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SloBertAA_Top20_WithoutOOC_082023_MultilingualBertBase
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2075
- Accuracy: 0.8470
- F1: 0.8471
- Precision: 0.8475
- Recall: 0.8470
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6541 | 1.0 | 22717 | 0.6481 | 0.7923 | 0.7920 | 0.8008 | 0.7923 |
| 0.5254 | 2.0 | 45434 | 0.5756 | 0.8198 | 0.8204 | 0.8268 | 0.8198 |
| 0.3977 | 3.0 | 68151 | 0.5874 | 0.8279 | 0.8285 | 0.8331 | 0.8279 |
| 0.3059 | 4.0 | 90868 | 0.6427 | 0.8357 | 0.8357 | 0.8378 | 0.8357 |
| 0.2596 | 5.0 | 113585 | 0.7435 | 0.8378 | 0.8377 | 0.8403 | 0.8378 |
| 0.1706 | 6.0 | 136302 | 0.8755 | 0.8413 | 0.8407 | 0.8415 | 0.8413 |
| 0.146 | 7.0 | 159019 | 1.0080 | 0.8397 | 0.8393 | 0.8405 | 0.8397 |
| 0.0945 | 8.0 | 181736 | 1.1210 | 0.8422 | 0.8423 | 0.8441 | 0.8422 |
| 0.0534 | 9.0 | 204453 | 1.1898 | 0.8448 | 0.8449 | 0.8457 | 0.8448 |
| 0.0286 | 10.0 | 227170 | 1.2075 | 0.8470 | 0.8471 | 0.8475 | 0.8470 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
