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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: 3.1861
- Accuracy: 0.4193
- Perplexity: 24.1930
- Bleu: 0.1440
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:|
| 6.0438 | 0.2806 | 500 | 5.9200 | 0.1897 | 372.4009 | 0.0359 |
| 5.0422 | 0.5612 | 1000 | 4.8934 | 0.2636 | 133.4091 | 0.0610 |
| 4.3494 | 0.8418 | 1500 | 4.2389 | 0.3183 | 69.3337 | 0.0833 |
| 3.9486 | 1.1223 | 2000 | 3.8856 | 0.3521 | 48.6953 | 0.1037 |
| 3.7605 | 1.4029 | 2500 | 3.7143 | 0.3671 | 41.0301 | 0.1206 |
| 3.6544 | 1.6835 | 3000 | 3.5898 | 0.3781 | 36.2282 | 0.1332 |
| 3.5527 | 1.9641 | 3500 | 3.5051 | 0.3862 | 33.2836 | 0.1349 |
| 3.4346 | 2.2447 | 4000 | 3.4410 | 0.3919 | 31.2181 | 0.1335 |
| 3.374 | 2.5253 | 4500 | 3.3867 | 0.3972 | 29.5672 | 0.1354 |
| 3.3442 | 2.8058 | 5000 | 3.3410 | 0.4017 | 28.2468 | 0.1405 |
| 3.2251 | 3.0864 | 5500 | 3.3072 | 0.4055 | 27.3093 | 0.1404 |
| 3.2187 | 3.3670 | 6000 | 3.2781 | 0.4088 | 26.5242 | 0.1401 |
| 3.1975 | 3.6476 | 6500 | 3.2494 | 0.4118 | 25.7753 | 0.1433 |
| 3.172 | 3.9282 | 7000 | 3.2276 | 0.4142 | 25.2178 | 0.1445 |
| 3.1055 | 4.2088 | 7500 | 3.2109 | 0.4163 | 24.8014 | 0.1447 |
| 3.0676 | 4.4893 | 8000 | 3.1977 | 0.4178 | 24.4763 | 0.1453 |
| 3.0779 | 4.7699 | 8500 | 3.1861 | 0.4193 | 24.1930 | 0.1440 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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