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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: GPT2-THESIS
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GPT2-THESIS
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9762
- F1: 0.7492
- Recall: 0.7492
- Accuracy: 0.7492
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
| 1.1822 | 1.0 | 1446 | 0.9362 | 0.7065 | 0.7065 | 0.7065 |
| 0.8791 | 2.0 | 2892 | 0.8616 | 0.7303 | 0.7303 | 0.7303 |
| 0.7218 | 3.0 | 4338 | 0.8250 | 0.7406 | 0.7406 | 0.7406 |
| 0.6025 | 4.0 | 5784 | 0.8351 | 0.7509 | 0.7509 | 0.7509 |
| 0.5142 | 5.0 | 7230 | 0.8781 | 0.7477 | 0.7477 | 0.7477 |
| 0.453 | 6.0 | 8676 | 0.8871 | 0.7526 | 0.7526 | 0.7526 |
| 0.3813 | 7.0 | 10122 | 0.9216 | 0.7475 | 0.7475 | 0.7475 |
| 0.3399 | 8.0 | 11568 | 0.9458 | 0.7477 | 0.7477 | 0.7477 |
| 0.3049 | 9.0 | 13014 | 0.9650 | 0.7504 | 0.7504 | 0.7504 |
| 0.2861 | 10.0 | 14460 | 0.9762 | 0.7492 | 0.7492 | 0.7492 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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