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---
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
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