---
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: 3.1859
- Accuracy: 0.4194
- Perplexity: 24.1889
- Bleu: 0.1461

## 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 | Accuracy | Bleu   | Validation Loss | Perplexity |
|:-------------:|:------:|:----:|:--------:|:------:|:---------------:|:----------:|
| 6.0432        | 0.2806 | 500  | 0.1909   | 0.0378 | 5.9180          | 371.6605   |
| 5.0476        | 0.5612 | 1000 | 0.2633   | 0.0612 | 4.8985          | 134.0910   |
| 4.3528        | 0.8418 | 1500 | 0.3182   | 0.0834 | 4.2398          | 69.3933    |
| 3.9497        | 1.1223 | 2000 | 0.3520   | 0.1054 | 3.8879          | 48.8078    |
| 3.7614        | 1.4029 | 2500 | 0.3674   | 0.1207 | 3.7128          | 40.9670    |
| 3.6543        | 1.6835 | 3000 | 0.3780   | 0.1310 | 3.5902          | 36.2404    |
| 3.5527        | 1.9641 | 3500 | 0.3864   | 0.1337 | 3.5048          | 33.2757    |
| 3.4348        | 2.2447 | 4000 | 0.3923   | 0.1361 | 3.4401          | 31.1898    |
| 3.3739        | 2.5253 | 4500 | 3.3868   | 0.3974 | 29.5718         | 0.1419     |
| 3.3441        | 2.8058 | 5000 | 3.3419   | 0.4020 | 28.2718         | 0.1394     |
| 3.2252        | 3.0864 | 5500 | 3.3067   | 0.4057 | 27.2940         | 0.1432     |
| 3.2188        | 3.3670 | 6000 | 3.2775   | 0.4088 | 26.5107         | 0.1421     |
| 3.1971        | 3.6476 | 6500 | 3.2502   | 0.4115 | 25.7958         | 0.1426     |
| 3.1722        | 3.9282 | 7000 | 3.2266   | 0.4143 | 25.1936         | 0.1446     |
| 3.1052        | 4.2088 | 7500 | 3.2103   | 0.4163 | 24.7864         | 0.1433     |
| 3.0672        | 4.4893 | 8000 | 3.1967   | 0.4180 | 24.4514         | 0.1438     |
| 3.0774        | 4.7699 | 8500 | 3.1859   | 0.4194 | 24.1889         | 0.1461     |


### Framework versions

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