metadata
license: mit
base_model: MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: zero-shot_text_classification_fine_tuned
results: []
zero-shot_text_classification_fine_tuned
This model is a fine-tuned version of MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6329
- Accuracy: 0.8235
- F1: 0.8241
- Log Loss: 0.6329
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Log Loss |
|---|---|---|---|---|---|---|
| No log | 1.0 | 375 | 1.1586 | 0.5505 | 0.5121 | 1.1586 |
| 1.4748 | 2.0 | 750 | 0.7917 | 0.7495 | 0.7506 | 0.7917 |
| 0.7813 | 3.0 | 1125 | 0.6692 | 0.798 | 0.7989 | 0.6692 |
| 0.5346 | 4.0 | 1500 | 0.6359 | 0.811 | 0.8105 | 0.6359 |
| 0.5346 | 5.0 | 1875 | 0.6329 | 0.8235 | 0.8241 | 0.6329 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0