metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: eng_cate
results: []
eng_cate
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2466
- Accuracy: 0.9159
- F1: 0.9159
- Precision: 0.9159
- Recall: 0.9159
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: 16
- eval_batch_size: 32
- 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 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 54 | 0.3248 | 0.9159 | 0.9159 | 0.9159 | 0.9159 |
| No log | 2.0 | 108 | 0.2950 | 0.9159 | 0.9159 | 0.9159 | 0.9159 |
| No log | 3.0 | 162 | 0.2577 | 0.9159 | 0.9159 | 0.9159 | 0.9159 |
| No log | 4.0 | 216 | 0.2557 | 0.9159 | 0.9159 | 0.9159 | 0.9159 |
| No log | 5.0 | 270 | 0.2466 | 0.9159 | 0.9159 | 0.9159 | 0.9159 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1