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HBERTv1_48_L6_H64_A2_emotion
This model is a fine-tuned version of gokuls/HBERTv1_48_L6_H64_A2 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.6476
- Accuracy: 0.7785
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 |
---|---|---|---|---|
1.6191 | 1.0 | 250 | 1.5064 | 0.481 |
1.4095 | 2.0 | 500 | 1.3079 | 0.526 |
1.1804 | 3.0 | 750 | 1.0961 | 0.6005 |
0.9849 | 4.0 | 1000 | 0.9269 | 0.6495 |
0.8587 | 5.0 | 1250 | 0.8335 | 0.717 |
0.7643 | 6.0 | 1500 | 0.7613 | 0.734 |
0.7015 | 7.0 | 1750 | 0.6982 | 0.761 |
0.6515 | 8.0 | 2000 | 0.6759 | 0.775 |
0.6182 | 9.0 | 2250 | 0.6590 | 0.7735 |
0.5991 | 10.0 | 2500 | 0.6476 | 0.7785 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0