deberta-v3-xsmall-Label_B-768-epochs-3
This model is a fine-tuned version of microsoft/deberta-v3-xsmall on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1073
- Accuracy: 0.9741
- F1: 0.9741
- Precision: 0.9755
- Recall: 0.9741
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.12 | 0.9994 | 1279 | 0.2452 | 0.9352 | 0.9350 | 0.9420 | 0.9352 |
0.0496 | 1.9996 | 2559 | 0.1073 | 0.9741 | 0.9741 | 0.9755 | 0.9741 |
0.0294 | 2.9982 | 3837 | 0.1162 | 0.9739 | 0.9739 | 0.9751 | 0.9739 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.5.0+cu124
- Datasets 2.18.0
- Tokenizers 0.19.1
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