deberta-v3-base-finetuned-m_express_emo
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4851
- Accuracy: 0.81
- F1: 0.8148
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.6862 | 1.0 | 26 | 0.6494 | 0.535 | 0.5439 |
0.6101 | 2.0 | 52 | 0.5192 | 0.795 | 0.7998 |
0.5095 | 3.0 | 78 | 0.4849 | 0.77 | 0.7805 |
0.4185 | 4.0 | 104 | 0.4783 | 0.815 | 0.8208 |
0.3871 | 5.0 | 130 | 0.4851 | 0.81 | 0.8148 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1
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Model tree for Gregorig/deberta-v3-base-finetuned-m_express_emo
Base model
microsoft/deberta-v3-base