metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-base-finetuned-autext23_s2
results: []
deberta-v3-base-finetuned-autext23_s2
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0620
- Accuracy: 0.5731
- F1: 0.5648
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 246 | 0.9935 | 0.5587 | 0.5371 |
| 1.1328 | 2.0 | 492 | 0.9254 | 0.5792 | 0.5592 |
| 1.1328 | 3.0 | 738 | 0.9501 | 0.5801 | 0.5692 |
| 0.7267 | 4.0 | 984 | 1.0345 | 0.5619 | 0.5509 |
| 0.7267 | 5.0 | 1230 | 1.0620 | 0.5731 | 0.5648 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1