metadata
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta-finetuned
results: []
deberta-finetuned
This model is a fine-tuned version of microsoft/deberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2989
- Accuracy: 0.9062
- F1: 0.9333
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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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 | 180 | 0.3227 | 0.8781 | 0.9150 |
| No log | 2.0 | 360 | 0.3293 | 0.8562 | 0.8940 |
| 0.3756 | 3.0 | 540 | 0.3180 | 0.8906 | 0.9210 |
| 0.3756 | 4.0 | 720 | 0.2866 | 0.9094 | 0.9357 |
| 0.3756 | 5.0 | 900 | 0.2989 | 0.9062 | 0.9333 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1