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

# finetuned_text_class

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: 0.4994
- Accuracy: 0.7702
- Recall: 0.8076
- Precision: 0.7557
- F1: 0.7808

## 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: 8e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.499         | 0.9961 | 193  | 0.4700          | 0.7602   | 0.7599 | 0.7652    | 0.7625 |
| 0.3852        | 1.9974 | 387  | 0.4994          | 0.7702   | 0.8076 | 0.7557    | 0.7808 |
| 0.1778        | 2.9987 | 581  | 0.6317          | 0.7638   | 0.6688 | 0.8320    | 0.7415 |
| 0.1007        | 4.0    | 775  | 0.8801          | 0.7609   | 0.7662 | 0.7628    | 0.7645 |
| 0.0567        | 4.9806 | 965  | 1.0289          | 0.7657   | 0.7586 | 0.7744    | 0.7664 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1