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---
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
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