---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: subcate-cs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# subcate-cs

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/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