---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
model-index:
- name: parallel-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-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: 3.2350
- Accuracy: 0.4161
- Perplexity: 25.4075
- Bleu: 0.1473

## 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   |
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:|
| 6.077         | 0.2806 | 500  | 5.9554          | 0.1870   | 385.8189   | 0.0352 |
| 5.1123        | 0.5612 | 1000 | 4.9836          | 0.2568   | 145.9931   | 0.0625 |
| 4.4123        | 0.8418 | 1500 | 4.3035          | 0.3159   | 73.9588    | 0.0843 |
| 4.0245        | 1.1223 | 2000 | 3.9678          | 0.3470   | 52.8693    | 0.1076 |
| 3.8298        | 1.4029 | 2500 | 3.7842          | 0.3630   | 44.0014    | 0.1166 |
| 3.7181        | 1.6835 | 3000 | 3.6620          | 0.3733   | 38.9404    | 0.1272 |
| 3.6123        | 1.9641 | 3500 | 3.5694          | 0.3818   | 35.4958    | 0.1311 |
| 3.4993        | 2.2447 | 4000 | 3.5029          | 0.3877   | 33.2118    | 0.1384 |
| 3.4358        | 2.5253 | 4500 | 3.4484          | 0.3930   | 31.4506    | 0.1358 |
| 3.4039        | 2.8058 | 5000 | 3.3989          | 0.3979   | 29.9323    | 0.1403 |
| 3.2908        | 3.0864 | 5500 | 3.3633          | 0.4018   | 28.8837    | 0.1409 |
| 3.2828        | 3.3670 | 6000 | 3.3326          | 0.4051   | 28.0103    | 0.1446 |
| 3.2606        | 3.6476 | 6500 | 3.3031          | 0.4081   | 27.1958    | 0.1457 |
| 3.234         | 3.9282 | 7000 | 3.2796          | 0.4106   | 26.5655    | 0.1433 |
| 3.1713        | 4.2088 | 7500 | 3.2621          | 0.4126   | 26.1045    | 0.1461 |
| 3.1314        | 4.4893 | 8000 | 3.2476          | 0.4145   | 25.7281    | 0.1455 |
| 3.1412        | 4.7699 | 8500 | 3.2350          | 0.4161   | 25.4075    | 0.1473 |


### Framework versions

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