---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: hr_cate
  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. -->

# hr_cate

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: 0.0404
- Accuracy: 0.7833
- F1: 0.8459
- Precision: 0.9146
- Recall: 0.7869

## 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: 32
- eval_batch_size: 64
- 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   | 227  | 0.0946          | 0.4140   | 0.5702 | 0.9179    | 0.4136 |
| No log        | 2.0   | 454  | 0.0573          | 0.6871   | 0.7845 | 0.9153    | 0.6864 |
| 0.1387        | 3.0   | 681  | 0.0468          | 0.7629   | 0.8291 | 0.9091    | 0.7620 |
| 0.1387        | 4.0   | 908  | 0.0420          | 0.7722   | 0.8372 | 0.9138    | 0.7725 |
| 0.0456        | 5.0   | 1135 | 0.0404          | 0.7833   | 0.8459 | 0.9146    | 0.7869 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1