---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tmppzxoh1ve
  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. -->

# tmppzxoh1ve

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1367
- Accuracy: 0.9661
- F1 Macro: 0.9659
- Accuracy Balanced: 0.9662
- F1 Micro: 0.9661
- Precision Macro: 0.9656
- Recall Macro: 0.9662
- Precision Micro: 0.9661
- Recall Micro: 0.9661

## 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: 80
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| No log        | 1.0   | 74   | 0.1516          | 0.9618   | 0.9614   | 0.9601            | 0.9618   | 0.9635          | 0.9601       | 0.9618          | 0.9618       |
| No log        | 2.0   | 148  | 0.1285          | 0.9745   | 0.9744   | 0.9744            | 0.9745   | 0.9744          | 0.9744       | 0.9745          | 0.9745       |
| No log        | 3.0   | 222  | 0.1230          | 0.9745   | 0.9743   | 0.9729            | 0.9745   | 0.9764          | 0.9729       | 0.9745          | 0.9745       |
| No log        | 4.0   | 296  | 0.1059          | 0.9713   | 0.9712   | 0.9709            | 0.9713   | 0.9714          | 0.9709       | 0.9713          | 0.9713       |
| No log        | 5.0   | 370  | 0.1226          | 0.9682   | 0.9680   | 0.9680            | 0.9682   | 0.9680          | 0.9680       | 0.9682          | 0.9682       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0