metadata
license: mit
base_model: MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: zeroshot-classification-test4
results: []
zeroshot-classification-test4
This model is a fine-tuned version of MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4552
- F1 Macro: 0.8589
- F1 Micro: 0.859
- Accuracy Balanced: 0.8590
- Accuracy: 0.859
- Precision Macro: 0.8596
- Recall Macro: 0.8590
- Precision Micro: 0.859
- Recall Micro: 0.859
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: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 313 | 0.3407 | 0.8507 | 0.851 | 0.8509 | 0.851 | 0.8534 | 0.8509 | 0.851 | 0.851 |
| 0.373 | 2.0 | 626 | 0.3830 | 0.8600 | 0.86 | 0.8600 | 0.86 | 0.86 | 0.8600 | 0.86 | 0.86 |
| 0.373 | 3.0 | 939 | 0.4552 | 0.8589 | 0.859 | 0.8590 | 0.859 | 0.8596 | 0.8590 | 0.859 | 0.859 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1