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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- recall
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- accuracy
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model-index:
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- name: GPT2-THESIS
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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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# GPT2-THESIS
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9762
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- F1: 0.7492
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- Recall: 0.7492
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- Accuracy: 0.7492
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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: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
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| 1.1822 | 1.0 | 1446 | 0.9362 | 0.7065 | 0.7065 | 0.7065 |
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| 0.8791 | 2.0 | 2892 | 0.8616 | 0.7303 | 0.7303 | 0.7303 |
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| 0.7218 | 3.0 | 4338 | 0.8250 | 0.7406 | 0.7406 | 0.7406 |
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| 0.6025 | 4.0 | 5784 | 0.8351 | 0.7509 | 0.7509 | 0.7509 |
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| 0.5142 | 5.0 | 7230 | 0.8781 | 0.7477 | 0.7477 | 0.7477 |
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| 0.453 | 6.0 | 8676 | 0.8871 | 0.7526 | 0.7526 | 0.7526 |
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| 0.3813 | 7.0 | 10122 | 0.9216 | 0.7475 | 0.7475 | 0.7475 |
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| 0.3399 | 8.0 | 11568 | 0.9458 | 0.7477 | 0.7477 | 0.7477 |
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| 0.3049 | 9.0 | 13014 | 0.9650 | 0.7504 | 0.7504 | 0.7504 |
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| 0.2861 | 10.0 | 14460 | 0.9762 | 0.7492 | 0.7492 | 0.7492 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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