---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: HW2_finetuned_model
  results: []
---

language: en

license: mit

# HW2_finetuned_model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1321
- Accuracy: 0.97
- F1: 0.9700
- Precision: 0.9717
- Recall: 0.97

## Model description

This model wwas used for text classification of the dataset found at huggingface.co/datasets/mrob937/desdep_text_dataset

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1276        | 1.0   | 120  | 0.2365          | 0.9458   | 0.9457 | 0.9511    | 0.9458 |
| 0.4081        | 2.0   | 240  | 0.2115          | 0.9583   | 0.9583 | 0.9615    | 0.9583 |
| 0.1085        | 3.0   | 360  | 0.1289          | 0.9708   | 0.9708 | 0.9724    | 0.9708 |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0