multibert2809_flow
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4534
- Precision: 0.7055
- Recall: 0.7076
- F1: 0.7066
- Accuracy: 0.8709
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: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 118 | 0.5021 | 0.6550 | 0.6229 | 0.6385 | 0.8414 |
| No log | 2.0 | 236 | 0.4534 | 0.7055 | 0.7076 | 0.7066 | 0.8709 |
| No log | 3.0 | 354 | 0.4903 | 0.7455 | 0.7237 | 0.7345 | 0.8752 |
| No log | 4.0 | 472 | 0.5158 | 0.7488 | 0.7327 | 0.7407 | 0.8755 |
| 0.3074 | 5.0 | 590 | 0.5685 | 0.7502 | 0.7434 | 0.7468 | 0.8758 |
| 0.3074 | 6.0 | 708 | 0.5799 | 0.7612 | 0.7530 | 0.7570 | 0.8809 |
| 0.3074 | 7.0 | 826 | 0.6022 | 0.7673 | 0.7494 | 0.7582 | 0.8791 |
| 0.3074 | 8.0 | 944 | 0.6054 | 0.7663 | 0.7554 | 0.7608 | 0.8840 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3