metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Frozen10-8epoch-BERT-multilingual-finetuned-CEFR_ner-3000news
results: []
Frozen10-8epoch-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: 0.6817
- Accuracy: 0.3506
- Precision: 0.5220
- Recall: 0.4650
- F1: 0.3491
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 | 0.8923 | 0.3134 | 0.4780 | 0.3506 | 0.2419 |
| No log | 2.0 | 264 | 0.7952 | 0.3291 | 0.5018 | 0.4007 | 0.2921 |
| No log | 3.0 | 396 | 0.7565 | 0.3354 | 0.5125 | 0.4119 | 0.2994 |
| 0.9121 | 4.0 | 528 | 0.7263 | 0.3417 | 0.5153 | 0.4392 | 0.3192 |
| 0.9121 | 5.0 | 660 | 0.7022 | 0.3463 | 0.5347 | 0.4435 | 0.3325 |
| 0.9121 | 6.0 | 792 | 0.6906 | 0.3482 | 0.5347 | 0.4519 | 0.3394 |
| 0.9121 | 7.0 | 924 | 0.6828 | 0.3503 | 0.5218 | 0.4655 | 0.3497 |
| 0.69 | 8.0 | 1056 | 0.6817 | 0.3506 | 0.5220 | 0.4650 | 0.3491 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1