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rubert-tiny2_finetuned_emotion_experiment
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: 0.3947
- Accuracy: 0.8616
- F1: 0.8577
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=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.651 | 1.0 | 54 | 0.5689 | 0.8172 | 0.8008 |
0.5355 | 2.0 | 108 | 0.4842 | 0.8486 | 0.8349 |
0.4561 | 3.0 | 162 | 0.4436 | 0.8590 | 0.8509 |
0.4133 | 4.0 | 216 | 0.4203 | 0.8590 | 0.8528 |
0.3709 | 5.0 | 270 | 0.4071 | 0.8564 | 0.8515 |
0.3346 | 6.0 | 324 | 0.3980 | 0.8564 | 0.8529 |
0.3153 | 7.0 | 378 | 0.3985 | 0.8590 | 0.8565 |
0.302 | 8.0 | 432 | 0.3967 | 0.8642 | 0.8619 |
0.2774 | 9.0 | 486 | 0.3958 | 0.8616 | 0.8575 |
0.2728 | 10.0 | 540 | 0.3959 | 0.8668 | 0.8644 |
0.2427 | 11.0 | 594 | 0.3962 | 0.8590 | 0.8550 |
0.2425 | 12.0 | 648 | 0.3959 | 0.8642 | 0.8611 |
0.2414 | 13.0 | 702 | 0.3959 | 0.8642 | 0.8611 |
0.2249 | 14.0 | 756 | 0.3949 | 0.8616 | 0.8582 |
0.2391 | 15.0 | 810 | 0.3947 | 0.8616 | 0.8577 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1