ternary_support_eval_base_227_voices_transcriptions
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5979
- Accuracy: 0.9130
- F1 Score: 0.8919
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: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 1.2416 | 1.0 | 204 | 1.3783 | 0.6957 | 0.5708 |
| 1.2416 | 2.0 | 408 | 1.4377 | 0.6957 | 0.5708 |
| 1.4314 | 3.0 | 612 | 1.4118 | 0.6957 | 0.5708 |
| 1.4314 | 4.0 | 816 | 1.2822 | 0.6957 | 0.5708 |
| 1.3906 | 5.0 | 1020 | 1.3876 | 0.6957 | 0.5708 |
| 1.3906 | 6.0 | 1224 | 0.9901 | 0.7391 | 0.7152 |
| 1.3906 | 7.0 | 1428 | 0.7957 | 0.8261 | 0.8116 |
| 1.0941 | 8.0 | 1632 | 0.8328 | 0.8696 | 0.8498 |
| 1.0941 | 9.0 | 1836 | 0.5979 | 0.9130 | 0.8919 |
| 0.5454 | 10.0 | 2040 | 0.6083 | 0.9130 | 0.8919 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for rezaFarsh/ternary_support_eval_base_227_voices_transcriptions
Base model
google-bert/bert-base-multilingual-uncased