---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

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: 1.0407
- Accuracy: 0.563
- F1: 0.5630
- Precision: 0.5631
- Recall: 0.563

## 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: 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0416        | 1.0   | 2500  | 1.0319          | 0.5479   | 0.5347 | 0.5392    | 0.5479 |
| 0.9488        | 2.0   | 5000  | 1.0248          | 0.5594   | 0.5535 | 0.5540    | 0.5594 |
| 0.8759        | 3.0   | 7500  | 1.0407          | 0.563    | 0.5630 | 0.5631    | 0.563  |
| 0.7576        | 4.0   | 10000 | 1.1242          | 0.5553   | 0.5539 | 0.5533    | 0.5553 |
| 0.6735        | 5.0   | 12500 | 1.2117          | 0.5528   | 0.5504 | 0.5500    | 0.5528 |
| 0.5951        | 6.0   | 15000 | 1.2677          | 0.5464   | 0.5442 | 0.5427    | 0.5464 |
| 0.5128        | 7.0   | 17500 | 1.4077          | 0.5401   | 0.5456 | 0.5570    | 0.5401 |
| 0.4343        | 8.0   | 20000 | 1.4986          | 0.5416   | 0.5433 | 0.5458    | 0.5416 |
| 0.3861        | 9.0   | 22500 | 1.5921          | 0.5402   | 0.5436 | 0.5497    | 0.5402 |
| 0.3713        | 10.0  | 25000 | 1.6282          | 0.5376   | 0.5401 | 0.5438    | 0.5376 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1