EmoCentricSarcBERT27FebRstate42AvgPadding
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: 0.7255
- Accuracy: 0.8850
- Precision: 0.8642
- Recall: 0.8362
- F1: 0.8500
- Mcc: 0.7570
- Roc Auc: 0.9530
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.3908 | 1.0 | 735 | 0.2959 | 0.8656 | 0.8680 | 0.7725 | 0.8175 | 0.7147 | 0.9440 |
| 0.2703 | 2.0 | 1470 | 0.2861 | 0.8754 | 0.8384 | 0.8428 | 0.8406 | 0.7384 | 0.9536 |
| 0.1360 | 3.0 | 2205 | 0.3375 | 0.8856 | 0.8391 | 0.8742 | 0.8563 | 0.7618 | 0.9572 |
| 0.1019 | 4.0 | 2940 | 0.4920 | 0.8817 | 0.8600 | 0.8319 | 0.8457 | 0.7501 | 0.9543 |
| 0.0529 | 5.0 | 3675 | 0.5989 | 0.8868 | 0.8722 | 0.8314 | 0.8513 | 0.7606 | 0.9543 |
| 0.0451 | 6.0 | 4410 | 0.6671 | 0.8855 | 0.8529 | 0.8533 | 0.8531 | 0.7592 | 0.9523 |
| 0.0258 | 7.0 | 5145 | 0.7255 | 0.8850 | 0.8642 | 0.8362 | 0.8500 | 0.7570 | 0.9530 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cpu
- Datasets 4.5.0
- Tokenizers 0.22.2