---
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: 2.3325
- Precision: 0.0395
- Recall: 0.182
- F1: 0.0649
- Accuracy: 0.8597

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 43   | 1.5592          | 0.0020    | 0.124  | 0.0040 | 0.3311   |
| No log        | 2.0   | 86   | 1.2689          | 0.0104    | 0.14   | 0.0193 | 0.6247   |
| No log        | 3.0   | 129  | 1.1742          | 0.0110    | 0.172  | 0.0206 | 0.6614   |
| No log        | 4.0   | 172  | 1.3716          | 0.0147    | 0.178  | 0.0271 | 0.6468   |
| No log        | 5.0   | 215  | 1.3265          | 0.0177    | 0.178  | 0.0323 | 0.7203   |
| No log        | 6.0   | 258  | 1.5835          | 0.0217    | 0.176  | 0.0386 | 0.7574   |
| No log        | 7.0   | 301  | 1.6678          | 0.0249    | 0.174  | 0.0435 | 0.7952   |
| No log        | 8.0   | 344  | 1.9432          | 0.0387    | 0.18   | 0.0636 | 0.8551   |
| No log        | 9.0   | 387  | 1.9371          | 0.0306    | 0.188  | 0.0526 | 0.7962   |
| No log        | 10.0  | 430  | 2.0129          | 0.0305    | 0.182  | 0.0523 | 0.8187   |
| No log        | 11.0  | 473  | 2.1952          | 0.0402    | 0.192  | 0.0664 | 0.8595   |
| 0.5993        | 12.0  | 516  | 2.1873          | 0.0369    | 0.182  | 0.0614 | 0.8512   |
| 0.5993        | 13.0  | 559  | 2.2653          | 0.0394    | 0.18   | 0.0646 | 0.8583   |
| 0.5993        | 14.0  | 602  | 2.3001          | 0.0397    | 0.184  | 0.0653 | 0.8553   |
| 0.5993        | 15.0  | 645  | 2.3325          | 0.0395    | 0.182  | 0.0649 | 0.8597   |


### Framework versions

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