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--- |
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license: other |
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library_name: peft |
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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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base_model: google/gemma-2b |
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datasets: |
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- generator |
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model-index: |
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- name: gemma2bit-sql |
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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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# gemma2bit-sql |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7133 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 1399 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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_steps: 10 |
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- training_steps: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.7834 | 0.02 | 5 | 1.5323 | |
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| 1.383 | 0.04 | 10 | 1.1950 | |
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| 1.1294 | 0.06 | 15 | 1.0211 | |
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| 0.964 | 0.08 | 20 | 0.9335 | |
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| 0.9112 | 0.09 | 25 | 0.8822 | |
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| 0.8775 | 0.11 | 30 | 0.8455 | |
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| 0.8375 | 0.13 | 35 | 0.8225 | |
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| 0.8109 | 0.15 | 40 | 0.8011 | |
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| 0.783 | 0.17 | 45 | 0.7862 | |
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| 0.7784 | 0.19 | 50 | 0.7738 | |
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| 0.7698 | 0.21 | 55 | 0.7625 | |
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| 0.7627 | 0.23 | 60 | 0.7524 | |
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| 0.7599 | 0.24 | 65 | 0.7461 | |
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| 0.7482 | 0.26 | 70 | 0.7406 | |
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| 0.7368 | 0.28 | 75 | 0.7338 | |
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| 0.7407 | 0.3 | 80 | 0.7293 | |
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| 0.7211 | 0.32 | 85 | 0.7243 | |
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| 0.718 | 0.34 | 90 | 0.7214 | |
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| 0.7187 | 0.36 | 95 | 0.7167 | |
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| 0.7251 | 0.38 | 100 | 0.7133 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
