hbertv1-emotion-intermediate_KD_new_2
This model is a fine-tuned version of gokuls/HBERTv1_48_L10_H768_A12 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 1.2346
- Accuracy: 0.897
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.954 | 1.0 | 250 | 1.8290 | 0.8255 |
| 1.775 | 2.0 | 500 | 1.6132 | 0.8285 |
| 1.5532 | 3.0 | 750 | 1.4540 | 0.8515 |
| 1.4101 | 4.0 | 1000 | 1.3212 | 0.8855 |
| 1.3138 | 5.0 | 1250 | 1.2489 | 0.8935 |
| 1.2434 | 6.0 | 1500 | 1.2280 | 0.896 |
| 1.1933 | 7.0 | 1750 | 1.2346 | 0.897 |
| 1.1417 | 8.0 | 2000 | 1.2159 | 0.8835 |
| 1.0954 | 9.0 | 2250 | 1.2792 | 0.8855 |
| 1.056 | 10.0 | 2500 | 1.2294 | 0.8875 |
| 1.0235 | 11.0 | 2750 | 1.2474 | 0.883 |
| 0.9943 | 12.0 | 3000 | 1.2179 | 0.886 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
gokuls/HBERTv1_48_L10_H768_A12