---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: group2_non_all_zero
  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. -->

# group2_non_all_zero

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3907
- Precision: 0.0415
- Recall: 0.086
- F1: 0.0560
- Accuracy: 0.9044

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 172  | 0.2512          | 0.0608    | 0.044  | 0.0510 | 0.9439   |
| No log        | 2.0   | 344  | 0.2667          | 0.0355    | 0.048  | 0.0408 | 0.9194   |
| 0.4561        | 3.0   | 516  | 0.2883          | 0.0445    | 0.078  | 0.0566 | 0.9198   |
| 0.4561        | 4.0   | 688  | 0.3610          | 0.0379    | 0.092  | 0.0537 | 0.8968   |
| 0.4561        | 5.0   | 860  | 0.3840          | 0.0528    | 0.094  | 0.0676 | 0.9095   |
| 0.1508        | 6.0   | 1032 | 0.3907          | 0.0415    | 0.086  | 0.0560 | 0.9044   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3