---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: group1_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. -->

# group1_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: 0.7437
- Precision: 0.0149
- Recall: 0.1076
- F1: 0.0262
- Accuracy: 0.9260

## 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   | 15   | 1.0746          | 0.0007    | 0.0633 | 0.0013 | 0.4145   |
| No log        | 2.0   | 30   | 0.8623          | 0.0023    | 0.1139 | 0.0045 | 0.6250   |
| No log        | 3.0   | 45   | 0.7242          | 0.0024    | 0.0696 | 0.0046 | 0.7334   |
| No log        | 4.0   | 60   | 0.6181          | 0.0037    | 0.0696 | 0.0070 | 0.8030   |
| No log        | 5.0   | 75   | 0.6489          | 0.0090    | 0.1329 | 0.0169 | 0.8282   |
| No log        | 6.0   | 90   | 0.6538          | 0.0091    | 0.1266 | 0.0170 | 0.8445   |
| No log        | 7.0   | 105  | 0.6189          | 0.0103    | 0.1013 | 0.0188 | 0.8893   |
| No log        | 8.0   | 120  | 0.6328          | 0.0101    | 0.1013 | 0.0183 | 0.8917   |
| No log        | 9.0   | 135  | 0.6561          | 0.0119    | 0.1076 | 0.0215 | 0.9099   |
| No log        | 10.0  | 150  | 0.6537          | 0.0152    | 0.1139 | 0.0267 | 0.9265   |
| No log        | 11.0  | 165  | 0.6939          | 0.0182    | 0.1139 | 0.0314 | 0.9385   |
| No log        | 12.0  | 180  | 0.7481          | 0.0113    | 0.0949 | 0.0203 | 0.9103   |
| No log        | 13.0  | 195  | 0.7242          | 0.0150    | 0.1203 | 0.0267 | 0.9209   |
| No log        | 14.0  | 210  | 0.7553          | 0.0140    | 0.1013 | 0.0247 | 0.9229   |
| No log        | 15.0  | 225  | 0.7437          | 0.0149    | 0.1076 | 0.0262 | 0.9260   |


### Framework versions

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