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

# DL_Audio_Hatespeech_text_classification_trainer_push

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: 1.6725
- Accuracy: 0.7641
- Recall: 0.7771
- Precision: 0.7620
- F1: 0.7695

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0191        | 1.0   | 97   | 1.5765          | 0.7483   | 0.8032 | 0.7281    | 0.7638 |
| 0.0351        | 2.0   | 194  | 1.2599          | 0.7428   | 0.8070 | 0.7195    | 0.7607 |
| 0.0451        | 3.0   | 291  | 1.1736          | 0.7580   | 0.7860 | 0.7488    | 0.7669 |
| 0.039         | 4.0   | 388  | 1.2600          | 0.7557   | 0.7592 | 0.7588    | 0.7590 |
| 0.039         | 5.0   | 485  | 1.1336          | 0.7606   | 0.7631 | 0.7640    | 0.7635 |
| 0.0199        | 6.0   | 582  | 1.4645          | 0.7593   | 0.7777 | 0.7546    | 0.7660 |
| 0.017         | 7.0   | 679  | 1.5825          | 0.7628   | 0.7096 | 0.7997    | 0.7519 |
| 0.0062        | 8.0   | 776  | 1.5688          | 0.7673   | 0.7510 | 0.7813    | 0.7658 |
| 0.0121        | 9.0   | 873  | 1.6285          | 0.7651   | 0.7510 | 0.7777    | 0.7641 |
| 0.0054        | 10.0  | 970  | 1.6725          | 0.7641   | 0.7771 | 0.7620    | 0.7695 |


### Framework versions

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