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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: 3.1859
- 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
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