---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sucidal-text-classification-distillbert
  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. -->

# sucidal-text-classification-distillbert

This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4590
- Accuracy: 0.8198
- F1 Score: 0.8198

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Score |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|
| 0.3602        | 0.1885 | 500  | 0.7867          | 0.7670   | 0.7670   |
| 0.6285        | 0.3769 | 1000 | 0.5574          | 0.7795   | 0.7795   |
| 0.5624        | 0.5654 | 1500 | 0.5011          | 0.7988   | 0.7988   |
| 0.5413        | 0.7539 | 2000 | 0.4968          | 0.8017   | 0.8017   |
| 0.5084        | 0.9423 | 2500 | 0.4712          | 0.8085   | 0.8085   |
| 0.4253        | 1.1308 | 3000 | 0.4938          | 0.8053   | 0.8053   |
| 0.3915        | 1.3193 | 3500 | 0.4781          | 0.8136   | 0.8136   |
| 0.3739        | 1.5077 | 4000 | 0.5195          | 0.8043   | 0.8043   |
| 0.3638        | 1.6962 | 4500 | 0.4790          | 0.8201   | 0.8201   |
| 0.3667        | 1.8847 | 5000 | 0.4590          | 0.8198   | 0.8198   |
| 0.3182        | 2.0731 | 5500 | 0.5129          | 0.8218   | 0.8218   |
| 0.2325        | 2.2616 | 6000 | 0.5279          | 0.8198   | 0.8198   |
| 0.2318        | 2.4501 | 6500 | 0.5368          | 0.8197   | 0.8197   |
| 0.2219        | 2.6385 | 7000 | 0.5606          | 0.8221   | 0.8221   |
| 0.2261        | 2.8270 | 7500 | 0.5406          | 0.8229   | 0.8229   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1