End of training
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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-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 [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: 1.1085
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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- optimizer: Use 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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| 1.0146 | 0.05 | 100 | 0.9460 |
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| 0.9847 | 0.1 | 200 | 0.9616 |
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| 0.608 | 0.15 | 300 | 0.9858 |
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| 0.9076 | 0.2 | 400 | 0.9852 |
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| 0.8904 | 0.25 | 500 | 1.0052 |
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| 0.5104 | 0.3 | 600 | 1.0349 |
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| 0.7794 | 0.35 | 700 | 1.0406 |
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| 0.744 | 0.4 | 800 | 1.0338 |
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| 0.569 | 0.45 | 900 | 1.0795 |
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| 0.6755 | 0.5 | 1000 | 1.0739 |
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| 0.5978 | 0.55 | 1100 | 1.0655 |
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| 0.749 | 0.6 | 1200 | 1.0841 |
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| 0.5411 | 0.65 | 1300 | 1.0907 |
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| 0.7742 | 0.7 | 1400 | 1.0923 |
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| 0.8629 | 0.75 | 1500 | 1.1010 |
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| 0.469 | 0.8 | 1600 | 1.1080 |
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| 0.7893 | 0.85 | 1700 | 1.1040 |
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| 0.7894 | 0.9 | 1800 | 1.1055 |
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| 0.4221 | 0.95 | 1900 | 1.1085 |
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| 0.7565 | 1.0 | 2000 | 1.1085 |
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.49.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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