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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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+
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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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+
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+ # peft-starcoder-lora-a100
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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