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

# eng_subcate

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: 0.0837
- Accuracy: 0.0
- F1: 0.0
- Precision: 0.0
- Recall: 0.0

## 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: 16
- 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   | 53   | 0.3166          | 0.0      | 0.0 | 0.0       | 0.0    |
| No log        | 2.0   | 106  | 0.1509          | 0.0      | 0.0 | 0.0       | 0.0    |
| No log        | 3.0   | 159  | 0.1024          | 0.0      | 0.0 | 0.0       | 0.0    |
| No log        | 4.0   | 212  | 0.0874          | 0.0      | 0.0 | 0.0       | 0.0    |
| No log        | 5.0   | 265  | 0.0837          | 0.0      | 0.0 | 0.0       | 0.0    |


### Framework versions

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