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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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- trl |
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- sft |
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- generated_from_trainer |
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base_model: Aravindan/gpt2out |
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datasets: |
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- generator |
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model-index: |
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- name: gpt2coder-instruct |
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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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# gpt2coder-instruct |
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This model is a fine-tuned version of [Aravindan/gpt2out](https://huggingface.co/Aravindan/gpt2out) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2879 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 10 |
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- total_train_batch_size: 80 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- training_steps: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.624 | 0.0147 | 30 | 2.4234 | |
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| 2.5018 | 0.0294 | 60 | 2.3461 | |
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| 2.4781 | 0.0441 | 90 | 2.2879 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
