FrozenLAST-8epoch-BERT-multilingual-finetuned-CEFR_ner-3000news
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4905
- Accuracy: 0.3967
- Precision: 0.4610
- Recall: 0.6222
- F1: 0.4287
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 132 | 0.6716 | 0.3464 | 0.4999 | 0.4456 | 0.3124 |
No log | 2.0 | 264 | 0.5548 | 0.3736 | 0.4556 | 0.5207 | 0.3660 |
No log | 3.0 | 396 | 0.5041 | 0.3844 | 0.4392 | 0.5635 | 0.3838 |
0.6267 | 4.0 | 528 | 0.4987 | 0.3885 | 0.4568 | 0.5729 | 0.4028 |
0.6267 | 5.0 | 660 | 0.4802 | 0.3938 | 0.4690 | 0.6042 | 0.4264 |
0.6267 | 6.0 | 792 | 0.4832 | 0.3953 | 0.4630 | 0.6112 | 0.4224 |
0.6267 | 7.0 | 924 | 0.4870 | 0.3952 | 0.4578 | 0.6174 | 0.4251 |
0.3073 | 8.0 | 1056 | 0.4905 | 0.3967 | 0.4610 | 0.6222 | 0.4287 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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