---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-tweet-disaster-classification
  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. -->

# bert-base-uncased-tweet-disaster-classification

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5396
- Accuracy: 0.8076

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 96   | 0.6598          | 0.7439   |
| No log        | 2.0   | 192  | 0.4624          | 0.8011   |
| No log        | 3.0   | 288  | 0.4350          | 0.8148   |
| No log        | 4.0   | 384  | 0.4326          | 0.8188   |
| No log        | 5.0   | 480  | 0.4331          | 0.8247   |
| 0.4631        | 6.0   | 576  | 0.4566          | 0.8227   |
| 0.4631        | 7.0   | 672  | 0.4711          | 0.8194   |
| 0.4631        | 8.0   | 768  | 0.5045          | 0.8102   |
| 0.4631        | 9.0   | 864  | 0.5400          | 0.8050   |
| 0.4631        | 10.0  | 960  | 0.5396          | 0.8076   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0