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--- |
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library_name: peft |
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license: bigcode-openrail-m |
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base_model: bigcode/starcoderbase-1b |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: starcoder-peft-airscript |
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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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# starcoder-peft-airscript |
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This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7155 |
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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: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 20 |
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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: 1700 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.2691 | 0.0588 | 100 | 1.1636 | |
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| 0.9655 | 0.1176 | 200 | 0.9384 | |
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| 0.8138 | 0.1765 | 300 | 0.8387 | |
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| 0.719 | 0.2353 | 400 | 0.7847 | |
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| 0.6408 | 0.2941 | 500 | 0.7503 | |
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| 0.5788 | 0.3529 | 600 | 0.7314 | |
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| 0.5386 | 0.4118 | 700 | 0.7168 | |
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| 0.4894 | 0.4706 | 800 | 0.7156 | |
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| 0.4583 | 0.5294 | 900 | 0.7101 | |
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| 0.4271 | 0.5882 | 1000 | 0.7070 | |
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| 0.4053 | 0.6471 | 1100 | 0.7117 | |
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| 0.3934 | 0.7059 | 1200 | 0.7123 | |
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| 0.379 | 0.7647 | 1300 | 0.7143 | |
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| 0.3666 | 0.8235 | 1400 | 0.7171 | |
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| 0.363 | 0.8824 | 1500 | 0.7171 | |
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| 0.3588 | 0.9412 | 1600 | 0.7163 | |
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| 0.357 | 1.0 | 1700 | 0.7155 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.45.2 |
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- Pytorch 2.5.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
