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--- |
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license: mit |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: EleutherAI/gpt-neo-1.3B |
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model-index: |
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- name: peft-starcoder-lora-a100 |
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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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# peft-starcoder-lora-a100 |
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This model is a fine-tuned version of [EleutherAI/gpt-neo-1.3B](https://huggingface.co/EleutherAI/gpt-neo-1.3B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9114 |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 30 |
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- training_steps: 2000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.4496 | 0.05 | 100 | 0.9015 | |
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| 0.9852 | 0.1 | 200 | 0.8839 | |
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| 0.7642 | 0.15 | 300 | 0.8856 | |
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| 1.1261 | 0.2 | 400 | 0.8876 | |
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| 0.8212 | 0.25 | 500 | 0.8850 | |
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| 0.6402 | 0.3 | 600 | 0.8740 | |
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| 0.6944 | 0.35 | 700 | 0.8867 | |
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| 0.7385 | 0.4 | 800 | 0.8854 | |
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| 0.821 | 0.45 | 900 | 0.8824 | |
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| 0.5807 | 0.5 | 1000 | 0.8902 | |
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| 0.8403 | 0.55 | 1100 | 0.8986 | |
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| 0.7615 | 0.6 | 1200 | 0.8962 | |
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| 0.5245 | 0.65 | 1300 | 0.8974 | |
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| 0.7926 | 0.7 | 1400 | 0.9113 | |
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| 0.7051 | 0.75 | 1500 | 0.9064 | |
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| 0.6337 | 0.8 | 1600 | 0.9068 | |
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| 0.5369 | 0.85 | 1700 | 0.9126 | |
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| 0.7193 | 0.9 | 1800 | 0.9144 | |
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| 0.7216 | 0.95 | 1900 | 0.9111 | |
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| 0.4985 | 1.0 | 2000 | 0.9114 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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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 |
