deberta-v3-large-emotion-multilabel-classifier-v2
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7907
- Macro F1: 0.4376
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 |
|---|---|---|---|---|
| 0.8072 | 1.0 | 2614 | 0.7889 | 0.4081 |
| 0.7284 | 2.0 | 5228 | 0.7816 | 0.4340 |
| 0.6588 | 3.0 | 7842 | 0.7907 | 0.4376 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for ngantuk-banget-wok/deberta-v3-large-emotion-multilabel-classifier-v2
Base model
microsoft/deberta-v3-large