---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
model-index:
- name: parallel-mean-bottleneck-gpt2-medium-wikitext
  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. -->

# parallel-mean-bottleneck-gpt2-medium-wikitext

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1864
- Accuracy: 0.4195
- Perplexity: 24.2005
- Bleu: 0.1476

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Perplexity | Bleu   |
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:|
| 6.0443        | 0.2806 | 500  | 5.9164          | 0.1901   | 371.0844   | 0.0350 |
| 5.0429        | 0.5612 | 1000 | 4.8947          | 0.2638   | 133.5839   | 0.0647 |
| 4.3531        | 0.8418 | 1500 | 4.2426          | 0.3176   | 69.5891    | 0.0829 |
| 3.9503        | 1.1223 | 2000 | 3.8874          | 0.3517   | 48.7842    | 0.1050 |
| 3.7613        | 1.4029 | 2500 | 3.7124          | 0.3672   | 40.9504    | 0.1211 |
| 3.6548        | 1.6835 | 3000 | 3.5911          | 0.3780   | 36.2753    | 0.1308 |
| 3.5531        | 1.9641 | 3500 | 3.5068          | 0.3860   | 33.3428    | 0.1340 |
| 3.4344        | 2.2447 | 4000 | 3.4411          | 0.3920   | 31.2224    | 0.1356 |
| 3.3743        | 2.5253 | 4500 | 3.3875          | 0.3972   | 29.5917    | 0.1389 |
| 3.3443        | 2.8058 | 5000 | 3.3429          | 0.4016   | 28.3017    | 0.1373 |
| 3.225         | 3.0864 | 5500 | 3.3080          | 0.4055   | 27.3310    | 0.1419 |
| 3.2185        | 3.3670 | 6000 | 3.2781          | 0.4090   | 26.5258    | 0.1463 |
| 3.1972        | 3.6476 | 6500 | 3.2500          | 0.4121   | 25.7899    | 0.1453 |
| 3.1719        | 3.9282 | 7000 | 3.2268          | 0.4144   | 25.1990    | 0.1465 |
| 3.1052        | 4.2088 | 7500 | 3.2109          | 0.4162   | 24.8018    | 0.1472 |
| 3.0672        | 4.4893 | 8000 | 3.1978          | 0.4179   | 24.4788    | 0.1469 |
| 3.0773        | 4.7699 | 8500 | 3.1864          | 0.4195   | 24.2005    | 0.1476 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0