metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: subcate-cs
results: []
subcate-cs
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: 0.0762
- Accuracy: 0.6868
- F1: 0.7105
- Precision: 0.7235
- Recall: 0.6980
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: 256
- 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 | 98 | 0.0743 | 0.6887 | 0.7074 | 0.7103 | 0.7044 |
| No log | 2.0 | 196 | 0.0753 | 0.6926 | 0.7141 | 0.7262 | 0.7025 |
| No log | 3.0 | 294 | 0.0751 | 0.6829 | 0.7078 | 0.7219 | 0.6942 |
| No log | 4.0 | 392 | 0.0774 | 0.6797 | 0.7009 | 0.7117 | 0.6903 |
| No log | 5.0 | 490 | 0.0762 | 0.6868 | 0.7105 | 0.7235 | 0.6980 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1