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hbertv2-emotion
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.4579
- Accuracy: 0.8865
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 |
|---|---|---|---|---|
| 1.3579 | 1.0 | 250 | 1.0703 | 0.608 |
| 0.762 | 2.0 | 500 | 0.6943 | 0.779 |
| 0.4828 | 3.0 | 750 | 0.5522 | 0.8135 |
| 0.3689 | 4.0 | 1000 | 0.4587 | 0.8645 |
| 0.2965 | 5.0 | 1250 | 0.4199 | 0.8745 |
| 0.256 | 6.0 | 1500 | 0.4329 | 0.874 |
| 0.2182 | 7.0 | 1750 | 0.4387 | 0.88 |
| 0.1842 | 8.0 | 2000 | 0.4304 | 0.8775 |
| 0.1575 | 9.0 | 2250 | 0.4405 | 0.88 |
| 0.1372 | 10.0 | 2500 | 0.4579 | 0.8865 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
