Mistral Finetune Api
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Mistral Fine-tuning API
Check out the docs: https://docs.mistral.ai/capabilities/finetuning/
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Prepare the dataset
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.
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total 147M -rw-r--r-- 1 root root 3.4K Jul 19 15:44 reformat_data.py drwxr-xr-x 1 root root 4.0K Jul 17 13:24 sample_data -rw-r--r-- 1 root root 698K Jul 19 16:05 ultrachat_chunk_eval.jsonl -rw-r--r-- 1 root root 146M Jul 19 16:05 ultrachat_chunk_train.jsonl
Reformat dataset
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:
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--2024-07-19 16:05:15-- https://raw.githubusercontent.com/mistralai/mistral-finetune/main/utils/reformat_data.py Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ... Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected. HTTP request sent, awaiting response... 200 OK Length: 3381 (3.3K) [text/plain] Saving to: ‘reformat_data.py.1’ reformat_data.py.1 100%[===================>] 3.30K --.-KB/s in 0s 2024-07-19 16:05:16 (42.2 MB/s) - ‘reformat_data.py.1’ saved [3381/3381]
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Skipped 3674th sample Skipped 9176th sample Skipped 10559th sample Skipped 13293th sample Skipped 13973th sample Skipped 15219th sample
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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'},
, {'content': '', 'role': 'assistant'},
, {'content': 'Can you help me find out the weight of the Sharp SMC1662DS microwave?', 'role': 'user'},
, {'content': 'Yes, the weight of the Sharp SMC1662DS microwave is 36.4 pounds.', 'role': 'assistant'},
, {'content': 'Can you tell me if the Sharp SMC1662DS microwave comes with a warranty?', 'role': 'user'},
, {'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'},
, {'content': 'Can you remind me of the innovative features of the Sharp SMC1662DS microwave?', 'role': 'user'}],
, dtype=object) Upload dataset
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{
"id": "da7305f6-d649-4fe2-8132-d6f17c7c8141",
"object": "file",
"bytes": 121379382,
"created_at": 1721405142,
"filename": "ultrachat_chunk_train.jsonl",
"sample_type": "instruct",
"source": "upload",
"purpose": null,
"num_lines": 28156
}
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{
"id": "f33adf06-8d79-420f-8722-d988cd60fbd6",
"object": "file",
"bytes": 596255,
"created_at": 1721405143,
"filename": "ultrachat_chunk_eval.jsonl",
"sample_type": "instruct",
"source": "upload",
"purpose": null,
"num_lines": 142
}
Create a fine-tuning job
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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))
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{
"id": "2c002adb-12be-4a5d-a3ef-baacf9025be9",
"auto_start": true,
"hyperparameters": {
"training_steps": 10,
"learning_rate": 0.0001,
"epochs": null,
"fim_ratio": null
},
"model": "open-mistral-7b",
"status": "QUEUED",
"job_type": "FT",
"created_at": 1721405164,
"modified_at": 1721405164,
"training_files": [
"da7305f6-d649-4fe2-8132-d6f17c7c8141"
],
"validation_files": [
"f33adf06-8d79-420f-8722-d988cd60fbd6"
],
"fine_tuned_model": null,
"suffix": null,
"integrations": [],
"trained_tokens": null,
"repositories": [],
"metadata": {
"expected_duration_seconds": null,
"cost": null,
"cost_currency": null,
"train_tokens_per_step": null,
"train_tokens": null,
"data_tokens": null,
"estimated_start_time": null
}
}
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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, 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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, 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[57]
DetailedJobOut(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), events=[EventOut(name='status-updated', created_at=1721405549, data=Unset()), EventOut(name='status-updated', created_at=1721405549, data=Unset()), EventOut(name='status-updated', created_at=1721405549, data=Unset()), EventOut(name='status-updated', created_at=1721405548, data=Unset()), EventOut(name='status-updated', created_at=1721405548, data=Unset())], checkpoints=[])
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Job is RUNNING, waiting 10 seconds
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Job is RUNNING, waiting 10 seconds
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Job is RUNNING, waiting 10 seconds
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Job is RUNNING, waiting 10 seconds
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"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!",
"tool_calls": null,
"prefix": false,
"role": "assistant"
}
}
]
}
Integration with Weights and Biases
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:
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