metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased
results: []
bert-base-multilingual-cased
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0379
- Precision: 0.9706
- Recall: 0.9753
- F1: 0.9729
- Accuracy: 0.9918
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0683 | 1.0 | 963 | 0.0550 | 0.9367 | 0.9505 | 0.9435 | 0.9839 |
| 0.0211 | 2.0 | 1926 | 0.0428 | 0.9580 | 0.9735 | 0.9657 | 0.9902 |
| 0.0098 | 3.0 | 2889 | 0.0379 | 0.9706 | 0.9753 | 0.9729 | 0.9918 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2