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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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datasets: |
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- generator |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Mistral-7B-text-to-sql-flash-attention-2-FAISS-10epoch |
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results: [] |
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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-flash-attention-2-FAISS-10epoch |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4891 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 8 |
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- total_train_batch_size: 24 |
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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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- lr_scheduler_warmup_steps: 15 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.1635 | 0.2005 | 10 | 0.7133 | |
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| 0.6525 | 0.4010 | 20 | 0.5602 | |
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| 0.5386 | 0.6015 | 30 | 0.5175 | |
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| 0.5042 | 0.8020 | 40 | 0.4926 | |
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| 0.487 | 1.0025 | 50 | 0.4839 | |
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| 0.4099 | 1.2030 | 60 | 0.4804 | |
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| 0.4078 | 1.4035 | 70 | 0.4748 | |
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| 0.4125 | 1.6040 | 80 | 0.4692 | |
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| 0.402 | 1.8045 | 90 | 0.4645 | |
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| 0.398 | 2.0050 | 100 | 0.4635 | |
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| 0.3066 | 2.2055 | 110 | 0.5003 | |
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| 0.3049 | 2.4060 | 120 | 0.4879 | |
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| 0.313 | 2.6065 | 130 | 0.4891 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
