---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-no_ear-loto_jews
  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-no_ear-loto_jews

This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5270

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 21
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 72.9514       | 0.03  | 10   | 65.3603         |
| 32.1127       | 0.06  | 20   | 18.4547         |
| 8.2152        | 0.08  | 30   | 6.7267          |
| 3.4911        | 0.11  | 40   | 2.9798          |
| 1.6339        | 0.14  | 50   | 1.2141          |
| 0.8984        | 0.17  | 60   | 0.9466          |
| 0.8166        | 0.2   | 70   | 0.7656          |
| 0.6533        | 0.23  | 80   | 0.6374          |
| 0.6208        | 0.25  | 90   | 0.6106          |
| 0.6942        | 0.28  | 100  | 0.5941          |
| 0.6241        | 0.31  | 110  | 0.5825          |
| 0.736         | 0.34  | 120  | 0.5790          |
| 0.5359        | 0.37  | 130  | 0.5745          |
| 0.6451        | 0.4   | 140  | 0.5694          |
| 0.5871        | 0.42  | 150  | 0.5625          |
| 0.6146        | 0.45  | 160  | 0.5635          |
| 0.5091        | 0.48  | 170  | 0.5578          |
| 0.5911        | 0.51  | 180  | 0.5580          |
| 0.5398        | 0.54  | 190  | 0.5528          |
| 0.6379        | 0.57  | 200  | 0.5484          |
| 0.5205        | 0.59  | 210  | 0.5481          |
| 0.5752        | 0.62  | 220  | 0.5448          |
| 0.6035        | 0.65  | 230  | 0.5419          |
| 0.5582        | 0.68  | 240  | 0.5417          |
| 0.5331        | 0.71  | 250  | 0.5407          |
| 0.5062        | 0.74  | 260  | 0.5398          |
| 0.562         | 0.76  | 270  | 0.5375          |
| 0.5845        | 0.79  | 280  | 0.5332          |
| 0.4904        | 0.82  | 290  | 0.5317          |
| 0.596         | 0.85  | 300  | 0.5303          |
| 0.5976        | 0.88  | 310  | 0.5298          |
| 0.5614        | 0.91  | 320  | 0.5284          |
| 0.6057        | 0.93  | 330  | 0.5287          |
| 0.4378        | 0.96  | 340  | 0.5290          |
| 0.6069        | 0.99  | 350  | 0.5267          |
| 0.4918        | 1.02  | 360  | 0.5291          |
| 0.5506        | 1.05  | 370  | 0.5315          |
| 0.4013        | 1.08  | 380  | 0.5270          |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.13.3