metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Frozen10-BERT-multilingual-finetuned-CEFR_ner-3000news
results: []
Frozen10-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: 0.6268
- Accuracy: 0.3626
- Precision: 0.5124
- Recall: 0.5049
- F1: 0.3803
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: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 132 | 0.8902 | 0.3136 | 0.4745 | 0.3572 | 0.2465 |
| No log | 2.0 | 264 | 0.7901 | 0.3298 | 0.4925 | 0.4019 | 0.2886 |
| No log | 3.0 | 396 | 0.7504 | 0.3365 | 0.5032 | 0.4185 | 0.2998 |
| 0.9069 | 4.0 | 528 | 0.7162 | 0.3434 | 0.5087 | 0.4450 | 0.3169 |
| 0.9069 | 5.0 | 660 | 0.6849 | 0.3498 | 0.4684 | 0.4536 | 0.3356 |
| 0.9069 | 6.0 | 792 | 0.6673 | 0.3537 | 0.5120 | 0.4640 | 0.3451 |
| 0.9069 | 7.0 | 924 | 0.6550 | 0.3562 | 0.4953 | 0.4866 | 0.3562 |
| 0.6585 | 8.0 | 1056 | 0.6505 | 0.3585 | 0.5117 | 0.4886 | 0.3572 |
| 0.6585 | 9.0 | 1188 | 0.6362 | 0.3601 | 0.5067 | 0.4987 | 0.3721 |
| 0.6585 | 10.0 | 1320 | 0.6317 | 0.3615 | 0.5095 | 0.5023 | 0.3773 |
| 0.6585 | 11.0 | 1452 | 0.6282 | 0.3622 | 0.5084 | 0.5052 | 0.3794 |
| 0.5862 | 12.0 | 1584 | 0.6268 | 0.3626 | 0.5124 | 0.5049 | 0.3803 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1