hbertv1-emotion-logit_KD-mini
This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_mini_freeze_new on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.4302
- Accuracy: 0.902
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 |
---|---|---|---|---|
2.0557 | 1.0 | 250 | 0.9294 | 0.8275 |
0.7977 | 2.0 | 500 | 0.5722 | 0.876 |
0.531 | 3.0 | 750 | 0.5091 | 0.8805 |
0.4472 | 4.0 | 1000 | 0.4683 | 0.8935 |
0.39 | 5.0 | 1250 | 0.4489 | 0.8975 |
0.3432 | 6.0 | 1500 | 0.4714 | 0.895 |
0.3148 | 7.0 | 1750 | 0.4302 | 0.902 |
0.2859 | 8.0 | 2000 | 0.4388 | 0.8955 |
0.2635 | 9.0 | 2250 | 0.4317 | 0.9 |
0.2409 | 10.0 | 2500 | 0.4433 | 0.901 |
0.2249 | 11.0 | 2750 | 0.4413 | 0.89 |
0.2159 | 12.0 | 3000 | 0.4607 | 0.897 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0
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