bert_uncased_L-8_H-256_A-4_emotion
This model is a fine-tuned version of google/bert_uncased_L-8_H-256_A-4 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1640
- Accuracy: 0.9445
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: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- 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 |
|---|---|---|---|---|
| 1.0879 | 1.0 | 250 | 0.4823 | 0.871 |
| 0.3595 | 2.0 | 500 | 0.2412 | 0.9215 |
| 0.2242 | 3.0 | 750 | 0.2043 | 0.925 |
| 0.1659 | 4.0 | 1000 | 0.1730 | 0.939 |
| 0.1355 | 5.0 | 1250 | 0.1583 | 0.9425 |
| 0.1133 | 6.0 | 1500 | 0.1635 | 0.94 |
| 0.0984 | 7.0 | 1750 | 0.1649 | 0.9385 |
| 0.0851 | 8.0 | 2000 | 0.1646 | 0.937 |
| 0.0785 | 9.0 | 2250 | 0.1640 | 0.9445 |
| 0.0716 | 10.0 | 2500 | 0.1650 | 0.9435 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1