<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
bert_emo_classifier
This model is a fine-tuned version of bert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.2748
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9063 | 0.25 | 500 | 0.4845 |
| 0.3362 | 0.5 | 1000 | 0.3492 |
| 0.2759 | 0.75 | 1500 | 0.2819 |
| 0.2521 | 1.0 | 2000 | 0.2464 |
| 0.1705 | 1.25 | 2500 | 0.2345 |
| 0.1841 | 1.5 | 3000 | 0.2013 |
| 0.1428 | 1.75 | 3500 | 0.1926 |
| 0.1747 | 2.0 | 4000 | 0.1866 |
| 0.1082 | 2.25 | 4500 | 0.2302 |
| 0.1142 | 2.5 | 5000 | 0.2118 |
| 0.1205 | 2.75 | 5500 | 0.2318 |
| 0.1135 | 3.0 | 6000 | 0.2306 |
| 0.0803 | 3.25 | 6500 | 0.2625 |
| 0.0745 | 3.5 | 7000 | 0.2850 |
| 0.085 | 3.75 | 7500 | 0.2719 |
| 0.0701 | 4.0 | 8000 | 0.2748 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.10.3
