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mistral finetune api
Details
File: mistral/fine_tune/mistral_finetune_api.ipynb
Type: Jupyter Notebook
Use Cases: Finetuning
Content
Notebook content (JSON format):
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "urSaPCZoqEmM"
},
"source": [
"# Mistral Fine-tuning API\n",
"\n",
"Check out the docs: https://docs.mistral.ai/capabilities/finetuning/"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "RUsq14W0qHuA"
},
"outputs": [],
"source": [
"!pip install mistralai pandas"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "27PpM60GqRvR"
},
"source": [
"## Prepare the dataset\n",
"\n",
"In this example, let’s use the ultrachat_200k dataset. We load a chunk of the data into Pandas Dataframes, split the data into training and validation, and save the data into the required jsonl format for fine-tuning."
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"id": "MUBRITvX59kC"
},
"outputs": [],
"source": [
"import pandas as pd\n",
"df = pd.read_parquet('https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k/resolve/main/data/test_gen-00000-of-00001-3d4cd8309148a71f.parquet')\n",
"\n",
"df_train=df.sample(frac=0.995,random_state=200)\n",
"df_eval=df.drop(df_train.index)\n",
"\n",
"df_train.to_json(\"ultrachat_chunk_train.jsonl\", orient=\"records\", lines=True)\n",
"df_eval.to_json(\"ultrachat_chunk_eval.jsonl\", orient=\"records\", lines=True)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "S1Pv9zx96CR5",
"outputId": "99f1db06-010b-4ce9-a827-0b4688d8dd0d"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total 147M\n",
"-rw-r--r-- 1 root root 3.4K Jul 19 15:44 reformat_data.py\n",
"drwxr-xr-x 1 root root 4.0K Jul 17 13:24 sample_data\n",
"-rw-r--r-- 1 root root 698K Jul 19 16:05 ultrachat_chunk_eval.jsonl\n",
"-rw-r--r-- 1 root root 146M Jul 19 16:05 ultrachat_chunk_train.jsonl\n"
]
}
],
"source": [
"!ls -lh"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "dVfIMwgUJF91"
},
"source": [
"## Reformat dataset\n",
"If you upload this ultrachat_chunk_train.jsonl to Mistral API, you might encounter an error message “Invalid file format” due to data formatting issues. To reformat the data into the correct format, you can download the reformat_dataset.py script and use it to validate and reformat both the training and evaluation data:"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kaLd2n726tAI",
"outputId": "3dc8c01c-540c-41c7-9ffc-f4a3988aa1d9"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2024-07-19 16:05:15-- https://raw.githubusercontent.com/mistralai/mistral-finetune/main/utils/reformat_data.py\n",
"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 3381 (3.3K) [text/plain]\n",
"Saving to: ‘reformat_data.py.1’\n",
"\n",
"reformat_data.py.1 100%[===================>] 3.30K --.-KB/s in 0s \n",
"\n",
"2024-07-19 16:05:16 (42.2 MB/s) - ‘reformat_data.py.1’ saved [3381/3381]\n",
"\n"
]
}
],
"source": [
"# download the validation and reformat script\n",
"!wget https://raw.githubusercontent.com/mistralai/mistral-finetune/main/utils/reformat_data.py"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "QvLwYwfl6vfc",
"outputId": "fd6318b7-d25e-47a1-b150-816c54f4278e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Skipped 3674th sample\n",
"Skipped 9176th sample\n",
"Skipped 10559th sample\n",
"Skipped 13293th sample\n",
"Skipped 13973th sample\n",
"Skipped 15219th sample\n"
]
}
],
"source": [
"# validate and reformat the training data\n",
"!python reformat_data.py ultrachat_chunk_train.jsonl"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"id": "gOKqvJMM6kgU"
},
"outputs": [],
"source": [
"# validate the reformat the eval data\n",
"!python reformat_data.py ultrachat_chunk_eval.jsonl"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "XO3RVA197Ont",
"outputId": "3ec0695e-748c-4527-feca-3be6a4ce60e5"
},
"outputs": [
{
"data": {
"text/plain": [
"array([{'content': 'What are the dimensions of the cavity, product, and shipping box of the Sharp SMC1662DS microwave?: With innovative features like preset controls, Sensor Cooking and the Carousel® turntable system, the Sharp® SMC1662DS 1.6 cu. Ft. Stainless Steel Carousel Countertop Microwave makes reheating your favorite foods, snacks and beverages easier than ever. Use popcorn and beverage settings for one-touch cooking. Express Cook allows one-touch cooking up to six minutes. The convenient and flexible \"+30 Sec\" key works as both instant start option and allows you to add more time during cooking.\\nThe Sharp SMC1662DS microwave is a bold design statement in any kitchen. The elegant, grey interior and bright white, LED interior lighting complements the stainless steel finish of this premium appliance.\\nCavity Dimensions (w x h x d): 15.5\" x 10.2\" x 17.1\"\\nProduct Dimensions (w x h x d): 21.8\" x 12.8\" x 17.7\"\\nShipping Dimensions (w x h x d) : 24.4\" x 15.0\" x 20.5\"', 'role': 'user'},\n",
" {'content': '', 'role': 'assistant'},\n",
" {'content': 'Can you help me find out the weight of the Sharp SMC1662DS microwave?', 'role': 'user'},\n",
" {'content': 'Yes, the weight of the Sharp SMC1662DS microwave is 36.4 pounds.', 'role': 'assistant'},\n",
" {'content': 'Can you tell me if the Sharp SMC1662DS microwave comes with a warranty?', 'role': 'user'},\n",
" {'content': 'Yes, the Sharp SMC1662DS microwave comes with a warranty. It has a 1-year limited warranty on parts and labor, a 4-year limited warranty on the magnetron tube, and an 8-year limited warranty on the magnetron tube for certain models. You should check the warranty details provided in the manual for complete information.', 'role': 'assistant'},\n",
" {'content': 'Can you remind me of the innovative features of the Sharp SMC1662DS microwave?', 'role': 'user'}],\n",
" dtype=object)"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_train.iloc[3674]['messages']"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hu_oLukAJect"
},
"source": [
"## Upload dataset"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"id": "B0UlO1Qa7xi3"
},
"outputs": [],
"source": [
"from mistralai import Mistral\n",
"import os\n",
"\n",
"api_key = os.environ[\"MISTRAL_API_KEY\"]\n",
"\n",
"client = Mistral(api_key=api_key)\n",
"\n",
"ultrachat_chunk_train = client.files.upload(file={\n",
" \"file_name\": \"ultrachat_chunk_train.jsonl\",\n",
" \"content\": open(\"ultrachat_chunk_train.jsonl\", \"rb\"),\n",
"})\n",
"ultrachat_chunk_eval = client.files.upload(file={\n",
" \"file_name\": \"ultrachat_chunk_eval.jsonl\",\n",
" \"content\": open(\"ultrachat_chunk_eval.jsonl\", \"rb\"),\n",
"})"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"id": "ChnYoKhoapES"
},
"outputs": [],
"source": [
"import json\n",
"def pprint(obj):\n",
" print(json.dumps(obj.dict(), indent=4))"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "rIAJdJIc9g2q",
"outputId": "fbaf9cc5-6c6e-4e44-ea66-815f6e15601a"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"id\": \"da7305f6-d649-4fe2-8132-d6f17c7c8141\",\n",
" \"object\": \"file\",\n",
" \"bytes\": 121379382,\n",
" \"created_at\": 1721405142,\n",
" \"filename\": \"ultrachat_chunk_train.jsonl\",\n",
" \"sample_type\": \"instruct\",\n",
" \"source\": \"upload\",\n",
" \"purpose\": null,\n",
" \"num_lines\": 28156\n",
"}\n"
]
}
],
"source": [
"pprint(ultrachat_chunk_train)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "5uA-Xnp1RTmx",
"outputId": "f8f8655a-f80a-436c-c8e0-53be71ac421f"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"id\": \"f33adf06-8d79-420f-8722-d988cd60fbd6\",\n",
" \"object\": \"file\",\n",
" \"bytes\": 596255,\n",
" \"created_at\": 1721405143,\n",
" \"filename\": \"ultrachat_chunk_eval.jsonl\",\n",
" \"sample_type\": \"instruct\",\n",
" \"source\": \"upload\",\n",
" \"purpose\": null,\n",
" \"num_lines\": 142\n",
"}\n"
]
}
],
"source": [
"pprint(ultrachat_chunk_eval)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "DqchXMeXJi6U"
},
"source": [
"## Create a fine-tuning job"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "x9Qk42ADRVKo",
"outputId": "b0a6f8ee-7368-466a-a5a7-ecd2fbdacd7d"
},
"outputs": [
{
"data": {
"text/plain": [
"JobOut(id='20178c3c-d75b-428e-b20d-7d39aa2b7468', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='QUEUED', job_type='FT', created_at=1721405548, modified_at=1721405548, training_files=['ec5af16a-77fe-4e14-ad09-47ead2848ce6'], validation_files=['d0c643a2-a57c-4031-bda7-5c9d6c3ec3e4'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None))"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"created_jobs = client.fine_tuning.jobs.create(\n",
" model=\"open-mistral-7b\",\n",
" training_files=[{\"file_id\": ultrachat_chunk_train.id, \"weight\": 1}],\n",
" validation_files=[ultrachat_chunk_eval.id],\n",
" hyperparameters={\n",
" \"training_steps\": 10,\n",
" \"learning_rate\":0.0001\n",
" },\n",
" auto_start=True\n",
")\n",
"created_jobs"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "bkZlYvwGanL1",
"outputId": "db1a66f9-908b-4d5f-c394-6ac744d8ec2f"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"id\": \"2c002adb-12be-4a5d-a3ef-baacf9025be9\",\n",
" \"auto_start\": true,\n",
" \"hyperparameters\": {\n",
" \"training_steps\": 10,\n",
" \"learning_rate\": 0.0001,\n",
" \"epochs\": null,\n",
" \"fim_ratio\": null\n",
" },\n",
" \"model\": \"open-mistral-7b\",\n",
" \"status\": \"QUEUED\",\n",
" \"job_type\": \"FT\",\n",
" \"created_at\": 1721405164,\n",
" \"modified_at\": 1721405164,\n",
" \"training_files\": [\n",
" \"da7305f6-d649-4fe2-8132-d6f17c7c8141\"\n",
" ],\n",
" \"validation_files\": [\n",
" \"f33adf06-8d79-420f-8722-d988cd60fbd6\"\n",
" ],\n",
" \"fine_tuned_model\": null,\n",
" \"suffix\": null,\n",
" \"integrations\": [],\n",
" \"trained_tokens\": null,\n",
" \"repositories\": [],\n",
" \"metadata\": {\n",
" \"expected_duration_seconds\": null,\n",
" \"cost\": null,\n",
" \"cost_currency\": null,\n",
" \"train_tokens_per_step\": null,\n",
" \"train_tokens\": null,\n",
" \"data_tokens\": null,\n",
" \"estimated_start_time\": null\n",
" }\n",
"}\n"
]
}
],
"source": [
"pprint(created_jobs)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "X8qv0CyKxEs2",
"outputId": "d713c1b0-1d8a-43ed-cc8c-5b8293d7bd9e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total=32 data=[JobOut(id='20178c3c-d75b-428e-b20d-7d39aa2b7468', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='RUNNING', job_type='FT', created_at=1721405548, modified_at=1721405549, training_files=['ec5af16a-77fe-4e14-ad09-47ead2848ce6'], validation_files=['d0c643a2-a57c-4031-bda7-5c9d6c3ec3e4'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=120, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='98cbe43b-61e5-47a8-a5fb-57f6d82abc0a', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='RUNNING', job_type='FT', created_at=1721405463, modified_at=1721405466, training_files=['71664e51-eae4-4c5b-9007-2c4586265609'], validation_files=['6c09517c-32d9-465c-8e4b-4496d1401ba0'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=120, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='baf7cb65-5ab6-4cdd-a4c6-a6f90c18cd7b', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1721396928, modified_at=1721397062, training_files=['96d5e16c-d701-455c-8f76-82054d005325'], validation_files=['cfc6dd29-f82e-48c0-8153-59e2313600c8'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240719:baf7cb65', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=100, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='7d82092d-a827-4943-9361-b321c6a3809c', auto_start=False, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='VALIDATED', job_type='FT', created_at=1721396750, modified_at=1721396751, training_files=['96d5e16c-d701-455c-8f76-82054d005325'], validation_files=['cfc6dd29-f82e-48c0-8153-59e2313600c8'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=100, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='1d69c7fc-fba8-40ad-92d1-3811b708cde1', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1721396736, modified_at=1721396871, training_files=['96d5e16c-d701-455c-8f76-82054d005325'], validation_files=['cfc6dd29-f82e-48c0-8153-59e2313600c8'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240719:1d69c7fc', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=100, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='64192a7e-b09a-4917-8760-015f90073a7b', auto_start=False, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='VALIDATED', job_type='FT', created_at=1721396729, modified_at=1721396730, training_files=['96d5e16c-d701-455c-8f76-82054d005325'], validation_files=['cfc6dd29-f82e-48c0-8153-59e2313600c8'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=100, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='adc708bd-877a-4201-bef1-16a1f1d93967', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1721396580, modified_at=1721396718, training_files=['96d5e16c-d701-455c-8f76-82054d005325'], validation_files=['cfc6dd29-f82e-48c0-8153-59e2313600c8'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240719:adc708bd', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=100, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='372926dc-6cea-4198-8234-bd9c1856a2e5', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1721396234, modified_at=1721396369, training_files=['96d5e16c-d701-455c-8f76-82054d005325'], validation_files=['cfc6dd29-f82e-48c0-8153-59e2313600c8'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240719:372926dc', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=140, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='bdfa52a5-3d66-4c51-bf37-b4ec6e4fa612', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=0.0431941570306258, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1721383368, modified_at=1721383502, training_files=['962f783d-d38a-46e2-aa7a-8826bf1a42f1'], validation_files=['1d6dbb85-09b6-4962-94f6-ae51f2353733'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240719:bdfa52a5', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=210, cost=2.6214, cost_currency='USD', train_tokens_per_step=131072, train_tokens=1310720, data_tokens=30344845, estimated_start_time=None)), JobOut(id='ded06fc3-7cf9-4753-a157-c2c3f9c0103b', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1720629436, modified_at=1720629567, training_files=['2f1e95bb-49cb-4998-9a2c-57a6093390ad'], validation_files=['dfeaa63b-55c5-4850-afd5-61ffebf26782'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240710:ded06fc3', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='d1587e39-eb2a-43ac-9f6b-4fa4d0e45c31', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1720629167, modified_at=1720629288, training_files=['93b01e13-1834-4a8b-b60a-5538d59b2c93'], validation_files=['2e1eb79d-388f-4c03-acfa-09b4bad51a91'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240710:d1587e39', suffix=None, integrations=[], trained_tokens=1310720, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='e89017e4-d038-4056-a869-73ee9e87c79e', auto_start=True, hyperparameters=TrainingParameters(training_steps=400, learning_rate=0.0003, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717576147, modified_at=1717593291, training_files=['8609ba12-353f-4277-87c8-0e1f7b6f72ce'], validation_files=['0c5f525a-8dce-4c70-abfd-6bff1ec8e0c0'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240605:e89017e4', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v8')], trained_tokens=52428800, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='3912b6ef-d2da-46b0-946f-56c243b8146f', auto_start=True, hyperparameters=TrainingParameters(training_steps=200, learning_rate=0.0003, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717576026, modified_at=1717584730, training_files=['8609ba12-353f-4277-87c8-0e1f7b6f72ce'], validation_files=['0c5f525a-8dce-4c70-abfd-6bff1ec8e0c0'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240605:3912b6ef', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v7')], trained_tokens=26214400, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='7d0c9b8c-d3c7-4890-9788-ea12b917cb46', auto_start=True, hyperparameters=TrainingParameters(training_steps=1500, learning_rate=7.5e-05, epochs=None, fim_ratio=None), model='mistral-small-latest', status='FAILED', job_type='FT', created_at=1717575567, modified_at=1717575890, training_files=['8609ba12-353f-4277-87c8-0e1f7b6f72ce'], validation_files=['0c5f525a-8dce-4c70-abfd-6bff1ec8e0c0'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v6')], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='1d50c69f-4ed5-4888-a05d-cea08e8a1e49', auto_start=True, hyperparameters=TrainingParameters(training_steps=800, learning_rate=7.5e-05, epochs=None, fim_ratio=None), model='mistral-small-latest', status='FAILED', job_type='FT', created_at=1717575373, modified_at=1717575868, training_files=['8609ba12-353f-4277-87c8-0e1f7b6f72ce'], validation_files=['0c5f525a-8dce-4c70-abfd-6bff1ec8e0c0'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v5')], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='56578b71-9952-445e-a1c4-a77e8970a396', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=7.5e-05, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717513741, modified_at=1717519351, training_files=['ab8a0a0e-699d-4084-a766-afd681c3e690'], validation_files=['9e48568e-0f51-48d0-bc87-dc45aaba6f4e'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240604:56578b71', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v4')], trained_tokens=16384000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='ee1ab18b-5333-4bbd-b329-7e3ab6e0112f', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=7.5e-05, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717513723, modified_at=1717519428, training_files=['ab8a0a0e-699d-4084-a766-afd681c3e690'], validation_files=['9e48568e-0f51-48d0-bc87-dc45aaba6f4e'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240604:ee1ab18b', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v4')], trained_tokens=16384000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='068ac05d-c6a6-445d-af61-a32417b846b5', auto_start=True, hyperparameters=TrainingParameters(training_steps=1500, learning_rate=0.0001, epochs=None, fim_ratio=None), model='mistral-small-latest', status='FAILED', job_type='FT', created_at=1717513568, modified_at=1717513655, training_files=['ab8a0a0e-699d-4084-a766-afd681c3e690'], validation_files=['9e48568e-0f51-48d0-bc87-dc45aaba6f4e'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v3')], trained_tokens=None, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='06f94d85-fb0f-443b-a4c3-9893ef4f8d41', auto_start=True, hyperparameters=TrainingParameters(training_steps=1500, learning_rate=0.0001, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717498861, modified_at=1717507124, training_files=['d6a724d5-4792-444a-8aba-c412da7a0a1c'], validation_files=['3e33c90e-6271-4307-b033-a7b72262957b'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240604:06f94d85', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v3')], trained_tokens=24576000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='7abfcf8f-6e99-486b-adc8-140cdc931874', auto_start=True, hyperparameters=TrainingParameters(training_steps=1500, learning_rate=0.0003, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717493002, modified_at=1717501386, training_files=['d6a724d5-4792-444a-8aba-c412da7a0a1c'], validation_files=['3e33c90e-6271-4307-b033-a7b72262957b'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240604:7abfcf8f', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v2')], trained_tokens=24576000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='9967f1a4-c985-4b29-acb8-05b17247ae1f', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=0.0001, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717453634, modified_at=1717459021, training_files=['502d7435-c6a7-4245-b6c5-33cd5eaf1fc5'], validation_files=['218f74d3-5961-460b-8452-59adc037231c'], OBJECT='job', fine_tuned_model=None, suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='economist_style_guide_v1')], trained_tokens=16384000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='adf036e3-69af-4762-bcd5-73b5226c2c64', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=0.0005, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717154159, modified_at=1717164477, training_files=['6438efb1-4ebc-4802-b67b-2f0069c5e4ec'], validation_files=['467c19ae-6000-4148-8cae-b8d42aa6068a'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240531:adf036e3', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='rapper_v0')], trained_tokens=32768000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='15a987eb-9bd6-479c-82bb-3a2582d5d0f2', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=0.0005, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717153851, modified_at=1717160771, training_files=['4a9a79b0-609c-4f94-b54e-82d0f9ef6037'], validation_files=['dd70766f-6d25-4e6f-a045-8753e9dfd896'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240531:15a987eb', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='socrates_v0')], trained_tokens=32768000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='00428354-ed52-450f-a299-0b47935d3ceb', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=0.0005, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717153185, modified_at=1717171939, training_files=['d1e4d2fc-c6ba-46ce-a070-0270b7a30012'], validation_files=['74884504-4a67-4806-adab-36a15d5e547a'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240531:00428354', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='call_assistant_v0')], trained_tokens=16384000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='50d006d4-3983-45ad-a071-56e070624eef', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=0.0005, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717153161, modified_at=1717158631, training_files=['d1e4d2fc-c6ba-46ce-a070-0270b7a30012'], validation_files=['74884504-4a67-4806-adab-36a15d5e547a'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240531:50d006d4', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='call_assistant_v0')], trained_tokens=32768000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='4ffddbce-caca-4dda-b49b-c1868213d141', auto_start=True, hyperparameters=TrainingParameters(training_steps=1000, learning_rate=0.0005, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717150637, modified_at=1717154822, training_files=['935a5891-500f-40d8-897d-bf917fcf9d51'], validation_files=['898df146-9f3b-48d3-9a4a-1740cff98748'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240531:4ffddbce', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='docstral_v3')], trained_tokens=32768000, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='48314f29-75f3-4b17-a8c6-bd8ce9128824', auto_start=True, hyperparameters=TrainingParameters(training_steps=300, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717148417, modified_at=1717150061, training_files=['935a5891-500f-40d8-897d-bf917fcf9d51'], validation_files=['898df146-9f3b-48d3-9a4a-1740cff98748'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240531:48314f29', suffix=None, integrations=[WandbIntegrationOut(project='test_api', TYPE='wandb', name=None, run_name='docstral_v2')], trained_tokens=9830400, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='a29e61db-40b2-42bf-9b2f-202059650474', auto_start=True, hyperparameters=TrainingParameters(training_steps=300, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717113860, modified_at=1717115931, training_files=['38fb0142-3811-4e17-b24b-7e62e8efda42'], validation_files=['a37a2cef-1404-46bf-98f4-2081abdb3470'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240531:a29e61db', suffix=None, integrations=[WandbIntegrationOut(project='patrick_api_test_docstral', TYPE='wandb', name=None, run_name='docstral')], trained_tokens=9830400, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='f88f46b9-c3df-4fd3-b991-0cc89201e1e1', auto_start=True, hyperparameters=TrainingParameters(training_steps=300, learning_rate=0.0001, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717113489, modified_at=1717125723, training_files=['38fb0142-3811-4e17-b24b-7e62e8efda42'], validation_files=['a37a2cef-1404-46bf-98f4-2081abdb3470'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240530:f88f46b9', suffix=None, integrations=[WandbIntegrationOut(project='patrick_api_test_docstral', TYPE='wandb', name=None, run_name='docstral')], trained_tokens=4915200, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='6ac4eb76-59a4-4840-a710-16667985b6bb', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=None, fim_ratio=None), model='mistral-small-latest', status='SUCCESS', job_type='FT', created_at=1717094735, modified_at=1717121456, training_files=['e44bcf12-b0fc-49c9-80dc-3095ec15e51e'], validation_files=['e44bcf12-b0fc-49c9-80dc-3095ec15e51e'], OBJECT='job', fine_tuned_model='ft:mistral-small-latest:b6e34a5e:20240530:6ac4eb76', suffix=None, integrations=[WandbIntegrationOut(project='patrick_api_test_mistral-small-latest', TYPE='wandb', name=None, run_name='ultrachat_')], trained_tokens=163840, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='f254559d-6f87-4ea9-83c1-cb98458a6046', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717094357, modified_at=1717095416, training_files=['dec8c42d-fa77-46b8-96a4-66b23720edac'], validation_files=['dec8c42d-fa77-46b8-96a4-66b23720edac'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240530:f254559d', suffix=None, integrations=[WandbIntegrationOut(project='patrick_api_test_open-mistral-7b', TYPE='wandb', name=None, run_name='ultrachat_')], trained_tokens=327680, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None)), JobOut(id='8f3d5c05-9beb-4a9c-9351-dbbd994e2fea', auto_start=True, hyperparameters=TrainingParameters(training_steps=10, learning_rate=0.0001, epochs=None, fim_ratio=None), model='open-mistral-7b', status='SUCCESS', job_type='FT', created_at=1717092822, modified_at=1717092973, training_files=['573626c4-2c77-4707-acec-afed94b8e0ff'], validation_files=['fbff9bc2-d938-4fda-bc84-26e551682ce1'], OBJECT='job', fine_tuned_model='ft:open-mistral-7b:b6e34a5e:20240530:8f3d5c05', suffix=None, integrations=[WandbIntegrationOut(project='patrick_test_dummy', TYPE='wandb', name=None, run_name=None)], trained_tokens=327680, repositories=[], metadata=JobMetadataOut(expected_duration_seconds=None, cost=None, cost_currency=None, train_tokens_per_step=None, train_tokens=None, data_tokens=None, estimated_start_time=None))] OBJECT='list'\n"
]
}
],
"source": [
"jobs = client.fine_tuning.jobs.list()\n",
"print(jobs)"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "M8X6Vk7RrTGt",
"outputId": "a8aa6694-17da-4565-8e79-0b2f691b4371"
},
"outputs": [
{
"data": {
"text/plain": [
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{
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" \"name\": \"status-updated\",\n",
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" },\n",
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" },\n",
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" },\n",
" {\n",
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" },\n",
" {\n",
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" \"created_at\": 1721405548\n",
" },\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405548\n",
" }\n",
" ],\n",
" \"checkpoints\": [\n",
" {\n",
" \"metrics\": {\n",
" \"train_loss\": 0.851776,\n",
" \"valid_loss\": 0.92623,\n",
" \"valid_mean_token_accuracy\": 1.900304\n",
" },\n",
" \"step_number\": 10,\n",
" \"created_at\": 1721405660\n",
" }\n",
" ]\n",
"}\n",
"Job is SUCCESS, waiting 10 seconds\n"
]
}
],
"source": [
"import time\n",
"\n",
"retrieved_job = client.fine_tuning.jobs.get(job_id = created_jobs.id)\n",
"while retrieved_job.status in [\"RUNNING\", \"QUEUED\"]:\n",
" retrieved_job = client.fine_tuning.jobs.get(job_id = created_jobs.id)\n",
" pprint(retrieved_job)\n",
" print(f\"Job is {retrieved_job.status}, waiting 10 seconds\")\n",
" time.sleep(10)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "_x6wRaDtXDzt",
"outputId": "c4060ad8-394b-46b0-ec93-a14c4671b257"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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" \"estimated_start_time\": null\n",
" }\n",
" },\n",
" {\n",
" \"id\": \"6ac4eb76-59a4-4840-a710-16667985b6bb\",\n",
" \"auto_start\": true,\n",
" \"hyperparameters\": {\n",
" \"training_steps\": 10,\n",
" \"learning_rate\": 0.0001,\n",
" \"epochs\": null,\n",
" \"fim_ratio\": null\n",
" },\n",
" \"model\": \"mistral-small-latest\",\n",
" \"status\": \"SUCCESS\",\n",
" \"job_type\": \"FT\",\n",
" \"created_at\": 1717094735,\n",
" \"modified_at\": 1717121456,\n",
" \"training_files\": [\n",
" \"e44bcf12-b0fc-49c9-80dc-3095ec15e51e\"\n",
" ],\n",
" \"validation_files\": [\n",
" \"e44bcf12-b0fc-49c9-80dc-3095ec15e51e\"\n",
" ],\n",
" \"fine_tuned_model\": \"ft:mistral-small-latest:b6e34a5e:20240530:6ac4eb76\",\n",
" \"suffix\": null,\n",
" \"integrations\": [\n",
" {\n",
" \"project\": \"patrick_api_test_mistral-small-latest\",\n",
" \"name\": null,\n",
" \"run_name\": \"ultrachat_\"\n",
" }\n",
" ],\n",
" \"trained_tokens\": 163840,\n",
" \"repositories\": [],\n",
" \"metadata\": {\n",
" \"expected_duration_seconds\": null,\n",
" \"cost\": null,\n",
" \"cost_currency\": null,\n",
" \"train_tokens_per_step\": null,\n",
" \"train_tokens\": null,\n",
" \"data_tokens\": null,\n",
" \"estimated_start_time\": null\n",
" }\n",
" },\n",
" {\n",
" \"id\": \"f254559d-6f87-4ea9-83c1-cb98458a6046\",\n",
" \"auto_start\": true,\n",
" \"hyperparameters\": {\n",
" \"training_steps\": 10,\n",
" \"learning_rate\": 0.0001,\n",
" \"epochs\": null,\n",
" \"fim_ratio\": null\n",
" },\n",
" \"model\": \"open-mistral-7b\",\n",
" \"status\": \"SUCCESS\",\n",
" \"job_type\": \"FT\",\n",
" \"created_at\": 1717094357,\n",
" \"modified_at\": 1717095416,\n",
" \"training_files\": [\n",
" \"dec8c42d-fa77-46b8-96a4-66b23720edac\"\n",
" ],\n",
" \"validation_files\": [\n",
" \"dec8c42d-fa77-46b8-96a4-66b23720edac\"\n",
" ],\n",
" \"fine_tuned_model\": \"ft:open-mistral-7b:b6e34a5e:20240530:f254559d\",\n",
" \"suffix\": null,\n",
" \"integrations\": [\n",
" {\n",
" \"project\": \"patrick_api_test_open-mistral-7b\",\n",
" \"name\": null,\n",
" \"run_name\": \"ultrachat_\"\n",
" }\n",
" ],\n",
" \"trained_tokens\": 327680,\n",
" \"repositories\": [],\n",
" \"metadata\": {\n",
" \"expected_duration_seconds\": null,\n",
" \"cost\": null,\n",
" \"cost_currency\": null,\n",
" \"train_tokens_per_step\": null,\n",
" \"train_tokens\": null,\n",
" \"data_tokens\": null,\n",
" \"estimated_start_time\": null\n",
" }\n",
" },\n",
" {\n",
" \"id\": \"8f3d5c05-9beb-4a9c-9351-dbbd994e2fea\",\n",
" \"auto_start\": true,\n",
" \"hyperparameters\": {\n",
" \"training_steps\": 10,\n",
" \"learning_rate\": 0.0001,\n",
" \"epochs\": null,\n",
" \"fim_ratio\": null\n",
" },\n",
" \"model\": \"open-mistral-7b\",\n",
" \"status\": \"SUCCESS\",\n",
" \"job_type\": \"FT\",\n",
" \"created_at\": 1717092822,\n",
" \"modified_at\": 1717092973,\n",
" \"training_files\": [\n",
" \"573626c4-2c77-4707-acec-afed94b8e0ff\"\n",
" ],\n",
" \"validation_files\": [\n",
" \"fbff9bc2-d938-4fda-bc84-26e551682ce1\"\n",
" ],\n",
" \"fine_tuned_model\": \"ft:open-mistral-7b:b6e34a5e:20240530:8f3d5c05\",\n",
" \"suffix\": null,\n",
" \"integrations\": [\n",
" {\n",
" \"project\": \"patrick_test_dummy\",\n",
" \"name\": null,\n",
" \"run_name\": null\n",
" }\n",
" ],\n",
" \"trained_tokens\": 327680,\n",
" \"repositories\": [],\n",
" \"metadata\": {\n",
" \"expected_duration_seconds\": null,\n",
" \"cost\": null,\n",
" \"cost_currency\": null,\n",
" \"train_tokens_per_step\": null,\n",
" \"train_tokens\": null,\n",
" \"data_tokens\": null,\n",
" \"estimated_start_time\": null\n",
" }\n",
" }\n",
" ],\n",
" \"OBJECT\": \"list\"\n",
"}\n"
]
}
],
"source": [
"# List jobs\n",
"jobs = client.fine_tuning.jobs.list()\n",
"pprint(jobs)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "OhTWA5uJXHNp",
"outputId": "b8adfe9d-baa6-4064-f215-b83c68ec7a9c"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"id\": \"20178c3c-d75b-428e-b20d-7d39aa2b7468\",\n",
" \"auto_start\": true,\n",
" \"hyperparameters\": {\n",
" \"training_steps\": 10,\n",
" \"learning_rate\": 0.0001,\n",
" \"epochs\": 0.0431941570306258,\n",
" \"fim_ratio\": null\n",
" },\n",
" \"model\": \"open-mistral-7b\",\n",
" \"status\": \"SUCCESS\",\n",
" \"job_type\": \"FT\",\n",
" \"created_at\": 1721405548,\n",
" \"modified_at\": 1721405693,\n",
" \"training_files\": [\n",
" \"ec5af16a-77fe-4e14-ad09-47ead2848ce6\"\n",
" ],\n",
" \"validation_files\": [\n",
" \"d0c643a2-a57c-4031-bda7-5c9d6c3ec3e4\"\n",
" ],\n",
" \"fine_tuned_model\": \"ft:open-mistral-7b:b6e34a5e:20240719:20178c3c\",\n",
" \"suffix\": null,\n",
" \"integrations\": [],\n",
" \"trained_tokens\": 1310720,\n",
" \"repositories\": [],\n",
" \"metadata\": {\n",
" \"expected_duration_seconds\": 120,\n",
" \"cost\": 2.6214,\n",
" \"cost_currency\": \"USD\",\n",
" \"train_tokens_per_step\": 131072,\n",
" \"train_tokens\": 1310720,\n",
" \"data_tokens\": 30344845,\n",
" \"estimated_start_time\": null\n",
" },\n",
" \"events\": [\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405693\n",
" },\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405549\n",
" },\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405549\n",
" },\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405549\n",
" },\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405548\n",
" },\n",
" {\n",
" \"name\": \"status-updated\",\n",
" \"created_at\": 1721405548\n",
" }\n",
" ],\n",
" \"checkpoints\": [\n",
" {\n",
" \"metrics\": {\n",
" \"train_loss\": 0.851776,\n",
" \"valid_loss\": 0.92623,\n",
" \"valid_mean_token_accuracy\": 1.900304\n",
" },\n",
" \"step_number\": 10,\n",
" \"created_at\": 1721405660\n",
" }\n",
" ]\n",
"}\n"
]
}
],
"source": [
"# Retrieve a jobs\n",
"retrieved_jobs = client.fine_tuning.jobs.get(job_id = created_jobs.id)\n",
"pprint(retrieved_jobs)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "LK-cSS2EJv-e"
},
"source": [
"## Use a fine-tuned model"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {
"id": "M8vRIB4yXQ5a"
},
"outputs": [],
"source": [
"chat_response = client.chat.complete(\n",
" model = retrieved_jobs.fine_tuned_model,\n",
" messages = [{\"role\":'user', \"content\":'What is the best French cheese?'}]\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "hp0oj5jvX0dP",
"outputId": "6d863d3d-eb4b-4410-fa45-040fa2023d48"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"id\": \"1fac96713fd74799922712e34e009f81\",\n",
" \"object\": \"chat.completion\",\n",
" \"model\": \"ft:open-mistral-7b:b6e34a5e:20240719:20178c3c\",\n",
" \"usage\": {\n",
" \"prompt_tokens\": 10,\n",
" \"completion_tokens\": 73,\n",
" \"total_tokens\": 83\n",
" },\n",
" \"created\": 1721405725,\n",
" \"choices\": [\n",
" {\n",
" \"index\": 0,\n",
" \"finish_reason\": \"stop\",\n",
" \"message\": {\n",
" \"content\": \"There isn't a single \\\"best\\\" French cheese as there are hundreds of different types of cheese to choose from, each with its unique taste and texture. Some popular French cheeses include Brie, Camembert, Roquefort, Comt\\u00e9, and Ch\\u00e8vre. Try different cheeses to find out the one you like best!\",\n",
" \"tool_calls\": null,\n",
" \"prefix\": false,\n",
" \"role\": \"assistant\"\n",
" }\n",
" }\n",
" ]\n",
"}\n"
]
}
],
"source": [
"pprint(chat_response)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "1xA68sx-J1Jj"
},
"source": [
"## Integration with Weights and Biases\n",
"We can also offer support for integration with Weights & Biases (W&B) to monitor and track various metrics and statistics associated with our fine-tuning jobs. To enable integration with W&B, you will need to create an account with W&B and add your W&B information in the “integrations” section in the job creation request:\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "L7ZYQzZ7YcYb"
},
"outputs": [],
"source": [
"client.fine_tuning.jobs.create(\n",
" model=\"open-mistral-7b\",\n",
" training_files=[{\"file_id\": ultrachat_chunk_train.id, \"weight\": 1}],\n",
" validation_files=[ultrachat_chunk_eval.id],\n",
" hyperparameters={\"training_steps\": 10, \"learning_rate\": 0.0001},\n",
" integrations=[\n",
" {\n",
" \"project\": \"<value>\",\n",
" \"api_key\": \"<value>\",\n",
" }\n",
" ]\n",
")"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}