phobert_55k_bo_vn
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2688
- Accuracy: 0.9534
- F1: 0.9536
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.211 | 1.0 | 1719 | 0.1383 | 0.9485 | 0.9487 |
0.1376 | 2.0 | 3438 | 0.1373 | 0.9521 | 0.9523 |
0.1105 | 3.0 | 5157 | 0.1431 | 0.9522 | 0.9527 |
0.0889 | 4.0 | 6876 | 0.1649 | 0.9534 | 0.9537 |
0.0715 | 5.0 | 8595 | 0.1770 | 0.9549 | 0.9548 |
0.0561 | 6.0 | 10314 | 0.1937 | 0.9533 | 0.9536 |
0.0443 | 7.0 | 12033 | 0.2260 | 0.9530 | 0.9533 |
0.0367 | 8.0 | 13752 | 0.2664 | 0.9529 | 0.9531 |
0.0327 | 9.0 | 15471 | 0.2663 | 0.9532 | 0.9534 |
0.0298 | 10.0 | 17190 | 0.2688 | 0.9534 | 0.9536 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
vinai/phobert-base-v2