metadata
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: fine_tuned_mBERT
results: []
fine_tuned_mBERT
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0788
- F1: 0.8387
- F5: 0.8492
- Precision: 0.8125
- Recall: 0.8667
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 11 | 0.2709 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 22 | 0.2130 | 0.1333 | 0.1002 | 1.0 | 0.0714 |
| No log | 3.0 | 33 | 0.1537 | 0.6207 | 0.6290 | 0.6 | 0.6429 |
| No log | 4.0 | 44 | 0.0986 | 0.7200 | 0.6884 | 0.8182 | 0.6429 |
| No log | 5.0 | 55 | 0.1376 | 0.7333 | 0.7525 | 0.6875 | 0.7857 |
| No log | 6.0 | 66 | 0.1490 | 0.6207 | 0.6290 | 0.6 | 0.6429 |
| No log | 7.0 | 77 | 0.1969 | 0.64 | 0.6120 | 0.7273 | 0.5714 |
| No log | 8.0 | 88 | 0.2131 | 0.6897 | 0.6989 | 0.6667 | 0.7143 |
| No log | 9.0 | 99 | 0.2097 | 0.6154 | 0.5978 | 0.6667 | 0.5714 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.17.1
- Tokenizers 0.15.2