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--- |
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license: other |
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base_model: yahma/llama-7b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: V0224O7 |
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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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# V0224O7 |
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This model is a fine-tuned version of [yahma/llama-7b-hf](https://huggingface.co/yahma/llama-7b-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7468 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.9764 | 0.13 | 10 | 1.5791 | |
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| 1.2349 | 0.26 | 20 | 1.0811 | |
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| 0.9773 | 0.39 | 30 | 0.9031 | |
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| 0.8686 | 0.52 | 40 | 0.8522 | |
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| 0.8333 | 0.65 | 50 | 0.8265 | |
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| 0.8084 | 0.78 | 60 | 0.8097 | |
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| 0.781 | 0.91 | 70 | 0.7957 | |
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| 0.766 | 1.04 | 80 | 0.7845 | |
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| 0.7282 | 1.17 | 90 | 0.7765 | |
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| 0.7412 | 1.3 | 100 | 0.7719 | |
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| 0.7302 | 1.43 | 110 | 0.7655 | |
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| 0.718 | 1.55 | 120 | 0.7614 | |
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| 0.709 | 1.68 | 130 | 0.7599 | |
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| 0.7202 | 1.81 | 140 | 0.7554 | |
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| 0.722 | 1.94 | 150 | 0.7504 | |
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| 0.6898 | 2.07 | 160 | 0.7513 | |
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| 0.6617 | 2.2 | 170 | 0.7508 | |
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| 0.6738 | 2.33 | 180 | 0.7474 | |
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| 0.6659 | 2.46 | 190 | 0.7470 | |
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| 0.6676 | 2.59 | 200 | 0.7478 | |
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| 0.6688 | 2.72 | 210 | 0.7469 | |
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| 0.6669 | 2.85 | 220 | 0.7468 | |
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| 0.669 | 2.98 | 230 | 0.7468 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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