---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: group3_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. -->

# group3_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: 2.0497
- Precision: 0.0638
- Recall: 0.2421
- F1: 0.1009
- Accuracy: 0.9339

## 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   | 55   | 1.1877          | 0.0140    | 0.25   | 0.0265 | 0.7339   |
| No log        | 2.0   | 110  | 0.9789          | 0.0219    | 0.2041 | 0.0395 | 0.8081   |
| No log        | 3.0   | 165  | 1.0274          | 0.0385    | 0.2437 | 0.0665 | 0.8703   |
| No log        | 4.0   | 220  | 1.1138          | 0.0225    | 0.1820 | 0.0401 | 0.8343   |
| No log        | 5.0   | 275  | 1.1690          | 0.0335    | 0.2184 | 0.0581 | 0.8702   |
| No log        | 6.0   | 330  | 1.3425          | 0.0421    | 0.2310 | 0.0712 | 0.8972   |
| No log        | 7.0   | 385  | 1.5089          | 0.0445    | 0.2342 | 0.0748 | 0.9079   |
| No log        | 8.0   | 440  | 1.5614          | 0.0466    | 0.2453 | 0.0783 | 0.9119   |
| No log        | 9.0   | 495  | 1.7200          | 0.0534    | 0.2453 | 0.0876 | 0.9220   |
| 0.5787        | 10.0  | 550  | 1.7086          | 0.0447    | 0.2453 | 0.0756 | 0.9098   |
| 0.5787        | 11.0  | 605  | 1.8784          | 0.0553    | 0.2342 | 0.0895 | 0.9263   |
| 0.5787        | 12.0  | 660  | 1.9659          | 0.0589    | 0.2421 | 0.0947 | 0.9299   |
| 0.5787        | 13.0  | 715  | 1.9472          | 0.0600    | 0.2437 | 0.0963 | 0.9297   |
| 0.5787        | 14.0  | 770  | 2.0058          | 0.0605    | 0.2373 | 0.0964 | 0.9310   |
| 0.5787        | 15.0  | 825  | 2.0497          | 0.0638    | 0.2421 | 0.1009 | 0.9339   |


### Framework versions

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