16_combo_webscrap_2109_v1_addgptdf
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1495
- Accuracy: 0.9568
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: 1e-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 |
|---|---|---|---|---|
| No log | 1.0 | 467 | 0.8510 | 0.7806 |
| 1.534 | 2.0 | 934 | 0.5037 | 0.8696 |
| 0.7131 | 3.0 | 1401 | 0.3481 | 0.9104 |
| 0.4879 | 4.0 | 1868 | 0.2717 | 0.9244 |
| 0.3665 | 5.0 | 2335 | 0.2324 | 0.9360 |
| 0.2948 | 6.0 | 2802 | 0.1949 | 0.9451 |
| 0.24 | 7.0 | 3269 | 0.1550 | 0.9566 |
| 0.1961 | 8.0 | 3736 | 0.1495 | 0.9568 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
google-bert/bert-base-multilingual-cased