bert-base-multilingual-uncased-finetuned-keyword
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 6.7290
- Accuracy: 0.0036
- Precision: 0.0015
- Recall: 0.0036
- F1: 0.0017
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 269 | 6.7517 | 0.0012 | 0.0000 | 0.0012 | 0.0000 |
| 6.7625 | 2.0 | 538 | 6.7499 | 0.0012 | 0.0000 | 0.0012 | 0.0000 |
| 6.7625 | 3.0 | 807 | 6.7366 | 0.0024 | 0.0003 | 0.0024 | 0.0005 |
| 6.7465 | 4.0 | 1076 | 6.7290 | 0.0036 | 0.0015 | 0.0036 | 0.0017 |
| 6.7465 | 5.0 | 1345 | 6.7276 | 0.0030 | 0.0015 | 0.0030 | 0.0013 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
google-bert/bert-base-multilingual-uncased