| --- |
| base_model: bigcode/starcoderbase-1b |
| library_name: peft |
| license: bigcode-openrail-m |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: mathpaper |
| results: [] |
| --- |
| |
|
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|
| # mathpaper |
|
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| This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on a dataset of 1000 arxiv category theory publications. |
|
|
| ## 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: |
| - learning_rate: 0.0005 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 30 |
| - training_steps: 2000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 1.3831 | 0.05 | 100 | 1.4326 | |
| | 1.2475 | 0.1 | 200 | 1.4149 | |
| | 1.2937 | 0.15 | 300 | 1.3903 | |
| | 1.3187 | 0.2 | 400 | 1.3723 | |
| | 1.4185 | 0.25 | 500 | 1.3577 | |
| | 1.3816 | 0.3 | 600 | 1.3475 | |
| | 1.324 | 0.35 | 700 | 1.3467 | |
| | 1.3456 | 0.4 | 800 | 1.3347 | |
| | 1.2906 | 0.45 | 900 | 1.3360 | |
| | 1.2916 | 0.5 | 1000 | 1.3315 | |
| | 1.3851 | 0.55 | 1100 | 1.3232 | |
| | 1.1827 | 0.6 | 1200 | 1.3193 | |
| | 1.2704 | 0.65 | 1300 | 1.3180 | |
| | 1.2495 | 0.7 | 1400 | 1.3104 | |
| | 1.2986 | 0.75 | 1500 | 1.3059 | |
| | 1.3759 | 0.8 | 1600 | 1.3005 | |
| | 1.2775 | 0.85 | 1700 | 1.2983 | |
| | 1.2648 | 0.9 | 1800 | 1.2969 | |
| | 1.2247 | 0.95 | 1900 | 1.2961 | |
| | 1.2152 | 1.0 | 2000 | 1.2959 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.13.2 |
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
