bert-base-greek-uncased-v1-finetuned-imdb
This model is a fine-tuned version of nlpaueb/bert-base-greek-uncased-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3617
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: 4
- eval_batch_size: 4
- 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 |
---|---|---|---|
1.0877 | 1.0 | 45 | 2.9871 |
1.2665 | 2.0 | 90 | 2.9228 |
1.9122 | 3.0 | 135 | 3.1228 |
2.2564 | 4.0 | 180 | 1.6066 |
1.9132 | 5.0 | 225 | 2.6351 |
1.9952 | 6.0 | 270 | 2.2649 |
1.7895 | 7.0 | 315 | 2.3376 |
2.0415 | 8.0 | 360 | 1.9894 |
1.8113 | 9.0 | 405 | 2.2998 |
1.6944 | 10.0 | 450 | 2.1420 |
1.7862 | 11.0 | 495 | 2.7167 |
1.5657 | 12.0 | 540 | 2.5103 |
1.4576 | 13.0 | 585 | 2.0238 |
1.3369 | 14.0 | 630 | 2.5880 |
1.3598 | 15.0 | 675 | 1.8161 |
1.3407 | 16.0 | 720 | 2.4031 |
1.3805 | 17.0 | 765 | 2.2539 |
1.176 | 18.0 | 810 | 3.2901 |
1.1152 | 19.0 | 855 | 2.3024 |
1.0629 | 20.0 | 900 | 2.0823 |
1.1972 | 21.0 | 945 | 2.9957 |
1.1317 | 22.0 | 990 | 2.5360 |
1.0396 | 23.0 | 1035 | 1.6268 |
0.8686 | 24.0 | 1080 | 3.2657 |
1.0526 | 25.0 | 1125 | 3.0398 |
0.9023 | 26.0 | 1170 | 2.8197 |
0.9539 | 27.0 | 1215 | 3.1922 |
0.8699 | 28.0 | 1260 | 1.6943 |
0.8669 | 29.0 | 1305 | 2.7801 |
0.7893 | 30.0 | 1350 | 2.1385 |
0.7462 | 31.0 | 1395 | 2.2881 |
0.7627 | 32.0 | 1440 | 3.0789 |
0.7536 | 33.0 | 1485 | 2.9320 |
0.8317 | 34.0 | 1530 | 3.4081 |
0.6749 | 35.0 | 1575 | 2.7531 |
0.789 | 36.0 | 1620 | 2.9154 |
0.6609 | 37.0 | 1665 | 2.1821 |
0.6795 | 38.0 | 1710 | 2.5330 |
0.6408 | 39.0 | 1755 | 3.4374 |
0.6827 | 40.0 | 1800 | 2.3127 |
0.6188 | 41.0 | 1845 | 2.0818 |
0.6085 | 42.0 | 1890 | 2.2737 |
0.6978 | 43.0 | 1935 | 2.9629 |
0.6164 | 44.0 | 1980 | 2.5250 |
0.6273 | 45.0 | 2025 | 2.3866 |
0.7064 | 46.0 | 2070 | 2.0937 |
0.6561 | 47.0 | 2115 | 2.4984 |
0.7341 | 48.0 | 2160 | 3.1911 |
0.6271 | 49.0 | 2205 | 2.2692 |
0.6757 | 50.0 | 2250 | 2.2642 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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