---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-Distilbert-Model
  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. -->

# distilbert-base-uncased-Distilbert-Model

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: 0.7383
- F1: 0.6823

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.848         | 0.5015 | 500  | 0.7910          | 0.6663 |
| 0.7872        | 1.0030 | 1000 | 0.7383          | 0.6823 |
| 0.6766        | 1.5045 | 1500 | 0.7502          | 0.7054 |
| 0.6854        | 2.0060 | 2000 | 0.7424          | 0.7096 |
| 0.5239        | 2.5075 | 2500 | 0.9047          | 0.7219 |
| 0.525         | 3.0090 | 3000 | 0.8375          | 0.7221 |
| 0.3925        | 3.5105 | 3500 | 1.0093          | 0.7216 |
| 0.4061        | 4.0120 | 4000 | 1.1403          | 0.7245 |
| 0.2928        | 4.5135 | 4500 | 1.3150          | 0.6862 |
| 0.3055        | 5.0150 | 5000 | 1.3811          | 0.7101 |
| 0.2184        | 5.5165 | 5500 | 1.5753          | 0.6985 |
| 0.23          | 6.0181 | 6000 | 1.5571          | 0.7122 |
| 0.1705        | 6.5196 | 6500 | 1.6771          | 0.7155 |
| 0.1416        | 7.0211 | 7000 | 1.7773          | 0.7089 |
| 0.1085        | 7.5226 | 7500 | 1.9134          | 0.7124 |
| 0.1437        | 8.0241 | 8000 | 1.8510          | 0.7118 |
| 0.0967        | 8.5256 | 8500 | 2.0276          | 0.7074 |
| 0.0733        | 9.0271 | 9000 | 2.1793          | 0.7112 |
| 0.0671        | 9.5286 | 9500 | 2.1100          | 0.7118 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cpu
- Datasets 2.20.0
- Tokenizers 0.19.1