---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
model-index:
- name: rotating-head-lr-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. -->

# rotating-head-lr-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: 3.2045
- Accuracy: 0.4189
- Perplexity: 24.6437
- Bleu: 0.1335

## 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   |
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:|
| 5.9064        | 0.2806 | 500  | 5.7488          | 0.2222   | 313.8089   | 0.0490 |
| 4.8623        | 0.5612 | 1000 | 4.7435          | 0.2805   | 114.8386   | 0.0709 |
| 4.3005        | 0.8418 | 1500 | 4.2307          | 0.3177   | 68.7669    | 0.0831 |
| 3.9583        | 1.1223 | 2000 | 3.9262          | 0.3464   | 50.7124    | 0.0916 |
| 3.7778        | 1.4029 | 2500 | 3.7522          | 0.3627   | 42.6128    | 0.1011 |
| 3.6805        | 1.6835 | 3000 | 3.6366          | 0.3738   | 37.9607    | 0.1052 |
| 3.5792        | 1.9641 | 3500 | 3.5434          | 0.3833   | 34.5829    | 0.1103 |
| 3.4655        | 2.2447 | 4000 | 3.4749          | 0.3900   | 32.2934    | 0.1168 |
| 3.4063        | 2.5253 | 4500 | 3.4235          | 0.3950   | 30.6766    | 0.1217 |
| 3.376         | 2.8058 | 5000 | 3.3767          | 0.4000   | 29.2745    | 0.1242 |
| 3.2591        | 3.0864 | 5500 | 3.3395          | 0.4039   | 28.2042    | 0.1258 |
| 3.2488        | 3.3670 | 6000 | 3.3072          | 0.4070   | 27.3098    | 0.1278 |
| 3.2244        | 3.6476 | 6500 | 3.2740          | 0.4109   | 26.4161    | 0.1309 |
| 3.1981        | 3.9282 | 7000 | 3.2526          | 0.4128   | 25.8571    | 0.1290 |
| 3.1294        | 4.2088 | 7500 | 3.2318          | 0.4156   | 25.3256    | 0.1293 |
| 3.0899        | 4.4893 | 8000 | 3.2180          | 0.4169   | 24.9787    | 0.1296 |
| 3.0993        | 4.7699 | 8500 | 3.2045          | 0.4189   | 24.6437    | 0.1335 |


### Framework versions

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