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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: distilgpt2-HC3
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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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# distilgpt2-HC3
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9983
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- Accuracy: 0.5441
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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: 0.001
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- train_batch_size: 8
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- eval_batch_size: 4
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- seed: 3208
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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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_ratio: 0.05
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- num_epochs: 6.0
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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 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.2485 | 0.98 | 41 | 2.1457 | 0.5158 |
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| 2.0757 | 1.98 | 82 | 2.0584 | 0.5304 |
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| 1.966 | 2.98 | 123 | 2.0210 | 0.5376 |
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| 1.8602 | 3.98 | 164 | 2.0012 | 0.5422 |
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| 1.8089 | 4.98 | 205 | 1.9977 | 0.5436 |
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| 1.7698 | 5.98 | 246 | 1.9983 | 0.5441 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.11.0+cu113
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- Datasets 2.6.1
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- Tokenizers 0.12.1
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