---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: reporting-multiclass
  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. -->

# reporting-multiclass

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1098
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0

## 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: 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.5931        | 1.0   | 33   | 0.4546          | 0.3988 | 0.6313  | 0.0      |
| 0.4492        | 2.0   | 66   | 0.3765          | 0.4629 | 0.6625  | 0.0446   |
| 0.3941        | 3.0   | 99   | 0.3113          | 0.6222 | 0.7403  | 0.0893   |
| 0.3004        | 4.0   | 132  | 0.2589          | 0.7948 | 0.8383  | 0.375    |
| 0.2581        | 5.0   | 165  | 0.2200          | 0.8741 | 0.8935  | 0.6071   |
| 0.2375        | 6.0   | 198  | 0.1922          | 0.9129 | 0.9302  | 0.6875   |
| 0.1881        | 7.0   | 231  | 0.1711          | 0.9333 | 0.9375  | 0.75     |
| 0.1806        | 8.0   | 264  | 0.1546          | 0.9390 | 0.9456  | 0.7857   |
| 0.164         | 9.0   | 297  | 0.1412          | 0.9654 | 0.9665  | 0.8661   |
| 0.1466        | 10.0  | 330  | 0.1309          | 0.9654 | 0.9665  | 0.8661   |
| 0.1318        | 11.0  | 363  | 0.1229          | 0.9772 | 0.9777  | 0.9107   |
| 0.13          | 12.0  | 396  | 0.1169          | 0.9933 | 0.9933  | 0.9732   |
| 0.1225        | 13.0  | 429  | 0.1129          | 1.0    | 1.0     | 1.0      |
| 0.1165        | 14.0  | 462  | 0.1106          | 1.0    | 1.0     | 1.0      |
| 0.1215        | 15.0  | 495  | 0.1098          | 1.0    | 1.0     | 1.0      |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1