metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: '5000'
results: []
5000
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: 0.1912
- Accuracy: 0.952
- Precision: 0.9751
- Recall: 0.9287
- F1: 0.9513
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.1936 | 0.939 | 0.9890 | 0.8891 | 0.9364 |
| No log | 2.0 | 126 | 0.2011 | 0.946 | 0.9747 | 0.9168 | 0.9449 |
| No log | 3.0 | 189 | 0.1912 | 0.952 | 0.9751 | 0.9287 | 0.9513 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu117
- Datasets 2.1.0
- Tokenizers 0.13.3