metadata
license: mit
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-xsmall-finetuned-DAGPap22
results: []
deberta-v3-xsmall-finetuned-DAGPap22
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: 0.1285
- Accuracy: 0.9794
- F1: 0.9850
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: 4.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 402 | 0.2610 | 0.9477 | 0.9621 |
| 0.4318 | 2.0 | 804 | 0.2039 | 0.9421 | 0.9559 |
| 0.1105 | 3.0 | 1206 | 0.1734 | 0.9664 | 0.9748 |
| 0.0451 | 4.0 | 1608 | 0.1000 | 0.9850 | 0.9890 |
| 0.0073 | 5.0 | 2010 | 0.1285 | 0.9794 | 0.9850 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1