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README.md
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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: peft-codelama-7b-qlora-scilab
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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-codelama-7b-qlora-scilab
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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: 0.6951
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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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| 0.7491 | 0.05 | 100 | 0.7142 |
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| 0.2948 | 0.1 | 200 | 0.6996 |
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| 0.4097 | 0.15 | 300 | 0.6878 |
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| 0.3277 | 0.2 | 400 | 0.6848 |
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| 0.2849 | 0.25 | 500 | 0.6813 |
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| 0.4167 | 0.3 | 600 | 0.6792 |
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| 0.2903 | 0.35 | 700 | 0.6812 |
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| 0.4744 | 0.4 | 800 | 0.6819 |
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| 0.4023 | 0.45 | 900 | 0.6815 |
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| 0.3235 | 0.5 | 1000 | 0.6817 |
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| 0.4935 | 0.55 | 1100 | 0.6850 |
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| 0.2069 | 0.6 | 1200 | 0.6857 |
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| 0.3495 | 0.65 | 1300 | 0.6863 |
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| 0.2526 | 0.7 | 1400 | 0.6900 |
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| 0.2146 | 0.75 | 1500 | 0.6923 |
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| 0.3677 | 0.8 | 1600 | 0.6951 |
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| 0.2449 | 0.85 | 1700 | 0.6950 |
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| 0.451 | 0.9 | 1800 | 0.6940 |
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| 0.348 | 0.95 | 1900 | 0.6952 |
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| 0.3009 | 1.0 | 2000 | 0.6951 |
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.48.3
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- Pytorch 2.5.1+cu124
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- Datasets 3.3.1
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- Tokenizers 0.21.0
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