rubert-tiny2_best_finetuned_emotion_experiment_augmented_anger_fear
This model is a fine-tuned version of cointegrated/rubert-tiny2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3902
- Accuracy: 0.8727
- F1: 0.8720
- Precision: 0.8718
- Recall: 0.8727
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=0.0001
- lr_scheduler_type: linear
- num_epochs: 40
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
1.3497 | 1.0 | 69 | 1.2944 | 0.5376 | 0.4665 | 0.6374 | 0.5376 |
1.2023 | 2.0 | 138 | 1.0370 | 0.7056 | 0.6745 | 0.7458 | 0.7056 |
0.9289 | 3.0 | 207 | 0.7437 | 0.8121 | 0.8082 | 0.8117 | 0.8121 |
0.6932 | 4.0 | 276 | 0.5717 | 0.8445 | 0.8428 | 0.8434 | 0.8445 |
0.5613 | 5.0 | 345 | 0.4888 | 0.8580 | 0.8572 | 0.8573 | 0.8580 |
0.469 | 6.0 | 414 | 0.4401 | 0.8633 | 0.8625 | 0.8623 | 0.8633 |
0.4176 | 7.0 | 483 | 0.4156 | 0.8653 | 0.8646 | 0.8644 | 0.8653 |
0.3724 | 8.0 | 552 | 0.4001 | 0.8706 | 0.8700 | 0.8699 | 0.8706 |
0.3427 | 9.0 | 621 | 0.3972 | 0.8706 | 0.8698 | 0.8701 | 0.8706 |
0.3243 | 10.0 | 690 | 0.3898 | 0.8737 | 0.8729 | 0.8736 | 0.8737 |
0.3039 | 11.0 | 759 | 0.3887 | 0.8716 | 0.8710 | 0.8717 | 0.8716 |
0.2803 | 12.0 | 828 | 0.3841 | 0.8716 | 0.8709 | 0.8709 | 0.8716 |
0.264 | 13.0 | 897 | 0.3872 | 0.8758 | 0.8753 | 0.8758 | 0.8758 |
0.2607 | 14.0 | 966 | 0.3837 | 0.8747 | 0.8743 | 0.8741 | 0.8747 |
0.2437 | 15.0 | 1035 | 0.3893 | 0.8716 | 0.8710 | 0.8712 | 0.8716 |
0.2358 | 16.0 | 1104 | 0.3867 | 0.8695 | 0.8691 | 0.8690 | 0.8695 |
0.2278 | 17.0 | 1173 | 0.3886 | 0.8737 | 0.8732 | 0.8732 | 0.8737 |
0.2143 | 18.0 | 1242 | 0.3902 | 0.8727 | 0.8720 | 0.8718 | 0.8727 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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