---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
model-index:
- name: rotating-head-gp-norm-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-gp-norm-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: 3.2113
- Accuracy: 0.4180
- Perplexity: 24.8108
- Bleu: 0.1307

## 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   |
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:|
| 5.9057        | 0.2806 | 500  | 5.7484          | 0.2234   | 313.6789   | 0.0477 |
| 4.8613        | 0.5612 | 1000 | 4.7455          | 0.2807   | 115.0632   | 0.0711 |
| 4.2976        | 0.8418 | 1500 | 4.2220          | 0.3187   | 68.1694    | 0.0837 |
| 3.9568        | 1.1223 | 2000 | 3.9271          | 0.3461   | 50.7582    | 0.0934 |
| 3.7919        | 1.4029 | 2500 | 3.7617          | 0.3626   | 43.0211    | 0.0942 |
| 3.692         | 1.6835 | 3000 | 3.6573          | 0.3725   | 38.7561    | 0.1052 |
| 3.5939        | 1.9641 | 3500 | 3.5628          | 0.3818   | 35.2616    | 0.1094 |
| 3.483         | 2.2447 | 4000 | 3.4932          | 0.3879   | 32.8924    | 0.1140 |
| 3.4251        | 2.5253 | 4500 | 3.4391          | 0.3933   | 31.1583    | 0.1204 |
| 3.3876        | 2.8058 | 5000 | 3.3855          | 0.3991   | 29.5323    | 0.1227 |
| 3.2719        | 3.0864 | 5500 | 3.3499          | 0.4020   | 28.5004    | 0.1246 |
| 3.2612        | 3.3670 | 6000 | 3.3160          | 0.4062   | 27.5488    | 0.1283 |
| 3.2373        | 3.6476 | 6500 | 3.2848          | 0.4095   | 26.7034    | 0.1288 |
| 3.2086        | 3.9282 | 7000 | 3.2598          | 0.4118   | 26.0453    | 0.1297 |
| 3.1402        | 4.2088 | 7500 | 3.2398          | 0.4146   | 25.5281    | 0.1344 |
| 3.1002        | 4.4893 | 8000 | 3.2246          | 0.4162   | 25.1447    | 0.1317 |
| 3.1099        | 4.7699 | 8500 | 3.2113          | 0.4180   | 24.8108    | 0.1307 |


### Framework versions

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