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---
tags:
- generated_from_trainer
base_model: nlpaueb/bert-base-greek-uncased-v1
model-index:
- name: bert-base-greek-uncased-v1-finetuned-polylex
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. -->
# bert-base-greek-uncased-v1-finetuned-polylex
This model is a fine-tuned version of [nlpaueb/bert-base-greek-uncased-v1](https://huggingface.co/nlpaueb/bert-base-greek-uncased-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1624
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1637 | 1.0 | 12 | 2.6649 |
| 3.0581 | 2.0 | 24 | 2.5475 |
| 2.648 | 3.0 | 36 | 2.1624 |
| 2.5983 | 4.0 | 48 | 2.3285 |
| 2.7524 | 5.0 | 60 | 2.5745 |
| 2.4923 | 6.0 | 72 | 2.8096 |
| 2.5336 | 7.0 | 84 | 2.9470 |
| 2.3271 | 8.0 | 96 | 2.5497 |
| 2.4018 | 9.0 | 108 | 2.3413 |
| 2.544 | 10.0 | 120 | 2.4170 |
| 1.9144 | 11.0 | 132 | 2.5254 |
| 2.0996 | 12.0 | 144 | 2.4147 |
| 1.8733 | 13.0 | 156 | 2.5462 |
| 1.8261 | 14.0 | 168 | 2.2045 |
| 2.0033 | 15.0 | 180 | 1.9549 |
| 1.9967 | 16.0 | 192 | 2.1614 |
| 1.8515 | 17.0 | 204 | 2.8167 |
| 1.8583 | 18.0 | 216 | 2.8441 |
| 1.7512 | 19.0 | 228 | 2.4536 |
| 1.5746 | 20.0 | 240 | 2.6204 |
| 1.5267 | 21.0 | 252 | 2.9290 |
| 1.7248 | 22.0 | 264 | 2.0433 |
| 1.5692 | 23.0 | 276 | 2.4710 |
| 1.6093 | 24.0 | 288 | 2.4340 |
| 1.619 | 25.0 | 300 | 2.2689 |
| 1.4406 | 26.0 | 312 | 3.6729 |
| 1.5452 | 27.0 | 324 | 3.2225 |
| 1.4575 | 28.0 | 336 | 1.8853 |
| 1.5534 | 29.0 | 348 | 2.2135 |
| 1.4872 | 30.0 | 360 | 2.7540 |
| 1.3923 | 31.0 | 372 | 2.2408 |
| 1.3682 | 32.0 | 384 | 2.5181 |
| 1.2623 | 33.0 | 396 | 2.1360 |
| 1.1888 | 34.0 | 408 | 2.3912 |
| 1.3427 | 35.0 | 420 | 2.4600 |
| 1.1969 | 36.0 | 432 | 2.6388 |
| 1.3367 | 37.0 | 444 | 2.5489 |
| 1.226 | 38.0 | 456 | 1.5805 |
| 1.1808 | 39.0 | 468 | 2.7466 |
| 1.1694 | 40.0 | 480 | 2.4887 |
| 1.2736 | 41.0 | 492 | 2.5735 |
| 1.2292 | 42.0 | 504 | 2.2357 |
| 1.2556 | 43.0 | 516 | 2.9244 |
| 1.0155 | 44.0 | 528 | 1.8348 |
| 1.2425 | 45.0 | 540 | 2.4494 |
| 1.2665 | 46.0 | 552 | 2.4866 |
| 1.3439 | 47.0 | 564 | 2.3430 |
| 1.4468 | 48.0 | 576 | 1.7801 |
| 1.1772 | 49.0 | 588 | 2.5785 |
| 1.0618 | 50.0 | 600 | 2.9959 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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