---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
model-index:
- name: parallel-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-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: 3.1010
- Accuracy: 0.4274
- Perplexity: 22.2205
- 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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   |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:----------:|:------:|
| 6.4455        | 0.1404 | 500   | 6.3313          | 0.1766   | 561.8647   | 0.0257 |
| 5.7254        | 0.2807 | 1000  | 5.6235          | 0.2136   | 276.8543   | 0.0454 |
| 5.1084        | 0.4211 | 1500  | 4.9822          | 0.2576   | 145.7898   | 0.0649 |
| 4.5994        | 0.5614 | 2000  | 4.5052          | 0.2929   | 90.4901    | 0.0741 |
| 4.2338        | 0.7018 | 2500  | 4.1378          | 0.3273   | 62.6674    | 0.0937 |
| 3.9975        | 0.8421 | 3000  | 3.9286          | 0.3465   | 50.8364    | 0.1031 |
| 3.8648        | 0.9825 | 3500  | 3.7926          | 0.3583   | 44.3697    | 0.1166 |
| 3.7164        | 1.1227 | 4000  | 3.6987          | 0.3667   | 40.3929    | 0.1226 |
| 3.6639        | 1.2630 | 4500  | 3.6221          | 0.3734   | 37.4157    | 0.1282 |
| 3.582         | 1.4034 | 5000  | 3.5575          | 0.3796   | 35.0763    | 0.1277 |
| 3.5315        | 1.5437 | 5500  | 3.5064          | 0.3840   | 33.3276    | 0.1312 |
| 3.5025        | 1.6841 | 6000  | 3.4594          | 0.3881   | 31.7989    | 0.1366 |
| 3.4462        | 1.8244 | 6500  | 3.4208          | 0.3919   | 30.5952    | 0.1310 |
| 3.4167        | 1.9648 | 7000  | 3.3863          | 0.3956   | 29.5564    | 0.1355 |
| 3.2967        | 2.1050 | 7500  | 3.3548          | 0.3989   | 28.6395    | 0.1317 |
| 3.2909        | 2.2453 | 8000  | 3.3290          | 0.4015   | 27.9115    | 0.1381 |
| 3.2593        | 2.3857 | 8500  | 3.3044          | 0.4039   | 27.2323    | 0.1422 |
| 3.2408        | 2.5260 | 9000  | 3.2826          | 0.4061   | 26.6448    | 0.1412 |
| 3.2278        | 2.6664 | 9500  | 3.2592          | 0.4090   | 26.0285    | 0.1436 |
| 3.2172        | 2.8067 | 10000 | 3.2415          | 0.4105   | 25.5733    | 0.1412 |
| 3.2145        | 2.9471 | 10500 | 3.2227          | 0.4125   | 25.0946    | 0.1402 |
| 3.0749        | 3.0873 | 11000 | 3.2099          | 0.4143   | 24.7768    | 0.1413 |
| 3.0777        | 3.2276 | 11500 | 3.1978          | 0.4160   | 24.4784    | 0.1420 |
| 3.0743        | 3.368  | 12000 | 3.1855          | 0.4174   | 24.1797    | 0.1438 |
| 3.0679        | 3.5084 | 12500 | 3.1735          | 0.4183   | 23.8912    | 0.1397 |
| 3.0635        | 3.6487 | 13000 | 3.1599          | 0.4200   | 23.5691    | 0.1423 |
| 3.0262        | 3.7891 | 13500 | 3.1489          | 0.4211   | 23.3095    | 0.1432 |
| 3.0382        | 3.9294 | 14000 | 3.1397          | 0.4223   | 23.0970    | 0.1461 |
| 2.9525        | 4.0696 | 14500 | 3.1335          | 0.4233   | 22.9539    | 0.1457 |
| 2.9621        | 4.2100 | 15000 | 3.1270          | 0.4239   | 22.8057    | 0.1454 |
| 2.9422        | 4.3503 | 15500 | 3.1211          | 0.4250   | 22.6718    | 0.1468 |
| 2.9224        | 4.4907 | 16000 | 3.1149          | 0.4257   | 22.5322    | 0.1454 |
| 2.9475        | 4.6310 | 16500 | 3.1084          | 0.4264   | 22.3862    | 0.1497 |
| 2.9318        | 4.7714 | 17000 | 3.1041          | 0.4270   | 22.2899    | 0.1468 |
| 2.9268        | 4.9117 | 17500 | 3.1010          | 0.4274   | 22.2205    | 0.1461 |


### Framework versions

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