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bert-base-uncased-finetuned-iemocap7
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9200
- Accuracy: 0.6712
- F1: 0.6795
It achieves the following results on the test set:
- Loss: 0.9468
- Accuracy: 0.67
- F1: 0.673
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: 4.319412088241492e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 51 | 1.0573 | 0.5412 | 0.5456 |
1.036 | 2.0 | 102 | 0.9216 | 0.6188 | 0.6267 |
1.036 | 3.0 | 153 | 0.9002 | 0.6625 | 0.6681 |
0.4819 | 4.0 | 204 | 0.8928 | 0.6663 | 0.6731 |
0.4819 | 5.0 | 255 | 0.9200 | 0.6712 | 0.6795 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2