metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: fin_cate
results: []
fin_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: 0.0523
- Accuracy: 0.9794
- F1: 0.9794
- Precision: 0.9794
- Recall: 0.9794
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: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 64 | 0.1458 | 0.9292 | 0.9292 | 0.9292 | 0.9292 |
| No log | 2.0 | 128 | 0.0591 | 0.9744 | 0.9744 | 0.9744 | 0.9744 |
| No log | 3.0 | 192 | 0.0488 | 0.9754 | 0.9754 | 0.9754 | 0.9754 |
| No log | 4.0 | 256 | 0.0487 | 0.9784 | 0.9788 | 0.9793 | 0.9784 |
| No log | 5.0 | 320 | 0.0500 | 0.9784 | 0.9784 | 0.9784 | 0.9784 |
| No log | 6.0 | 384 | 0.0506 | 0.9794 | 0.9794 | 0.9794 | 0.9794 |
| No log | 7.0 | 448 | 0.0523 | 0.9794 | 0.9794 | 0.9794 | 0.9794 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1