EmoCentricMaxEmoji73
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7203
- Accuracy: 0.8998
- Precision: 0.8995
- Recall: 0.8885
- F1: 0.8933
- Mcc: 0.7879
- Roc Auc: 0.9591
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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: tpu
- optimizer: Use OptimizerNames.ADAMW_TORCH_XLA with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Mcc | Roc Auc |
|---|---|---|---|---|---|---|---|---|---|
| 0.3531 | 1.0 | 735 | 0.2665 | 0.8812 | 0.8742 | 0.8774 | 0.8757 | 0.7516 | 0.9511 |
| 0.2689 | 2.0 | 1470 | 0.2552 | 0.8955 | 0.8974 | 0.8816 | 0.8881 | 0.7789 | 0.9610 |
| 0.1361 | 3.0 | 2205 | 0.2970 | 0.8924 | 0.8869 | 0.8869 | 0.8869 | 0.7739 | 0.9595 |
| 0.1047 | 4.0 | 2940 | 0.3781 | 0.8998 | 0.8974 | 0.8907 | 0.8938 | 0.7881 | 0.9599 |
| 0.0507 | 5.0 | 3675 | 0.4962 | 0.8952 | 0.8958 | 0.8825 | 0.8880 | 0.7781 | 0.9530 |
| 0.0454 | 6.0 | 4410 | 0.5965 | 0.8960 | 0.8895 | 0.8931 | 0.8912 | 0.7826 | 0.9612 |
| 0.0256 | 7.0 | 5145 | 0.7018 | 0.8974 | 0.8961 | 0.8869 | 0.8909 | 0.7829 | 0.9583 |
| 0.0202 | 8.0 | 5880 | 0.7203 | 0.8998 | 0.8995 | 0.8885 | 0.8933 | 0.7879 | 0.9591 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cpu
- Datasets 4.6.1
- Tokenizers 0.22.2