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--- |
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license: apache-2.0 |
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library_name: transformers |
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base_model: mistralai/Mistral-7B-v0.1 |
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datasets: |
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- b-mc2/sql-create-context |
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model-index: |
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- name: mistral-7b-text-to-sql_full-model |
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results: [] |
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reference: |
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- https://www.philschmid.de/fine-tune-llms-in-2024-with-trl |
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language: |
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- en |
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pipeline_tag: text2text-generation |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# mistral-7b-text-to-sql_full-model |
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- This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the b-mc2/sql-create-context dataset. |
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- These are the full model weights (merged with adapter weights), and the code to use these for generation is given below. |
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- Primary reference: https://www.philschmid.de/fine-tune-llms-in-2024-with-trl |
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## Model description |
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- Model type: Language model |
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- Language(s) (NLP): English |
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- License: Apache 2.0 |
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- Finetuned from model : Mistral-7B-v0.1 |
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## How to get started with the model |
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```python |
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import torch |
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from datasets import load_dataset |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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# Load model directly |
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tokenizer = AutoTokenizer.from_pretrained("delayedkarma/mistral-7b-text-to-sql_full-model") |
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model = AutoModelForCausalLM.from_pretrained("delayedkarma/mistral-7b-text-to-sql_full-model") |
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text = "How many matched scored 3–6, 7–6(5), 6–3?" |
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inputs = tokenizer(text, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=40) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 3 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 6 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 3 |
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### Framework versions |
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- PEFT 0.7.2.dev0 |
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- Transformers 4.36.2 |
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- Pytorch 2.2.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
