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: 0.2464
- Accuracy: 0.925
- F1: 0.9496
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 | 190 | 0.2784 | 0.9125 | 0.9412 |
| No log | 2.0 | 380 | 0.2370 | 0.9313 | 0.9536 |
| 0.3907 | 3.0 | 570 | 0.2328 | 0.925 | 0.9500 |
| 0.3907 | 4.0 | 760 | 0.2659 | 0.925 | 0.9504 |
| 0.3907 | 5.0 | 950 | 0.2464 | 0.925 | 0.9496 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1