---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-tweet-disaster
  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-tweet-disaster

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9563
- Accuracy: 0.8320
- F1: 0.8095

## 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: 64
- eval_batch_size: 64
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.605         | 1.0   | 108  | 0.4455          | 0.8123   | 0.7741 |
| 0.3878        | 2.0   | 216  | 0.3940          | 0.8438   | 0.8126 |
| 0.3228        | 3.0   | 324  | 0.4441          | 0.8241   | 0.8006 |
| 0.2526        | 4.0   | 432  | 0.4714          | 0.8333   | 0.8006 |
| 0.2002        | 5.0   | 540  | 0.5677          | 0.8189   | 0.7890 |
| 0.1391        | 6.0   | 648  | 0.6633          | 0.8307   | 0.8000 |
| 0.0922        | 7.0   | 756  | 0.8019          | 0.8294   | 0.8071 |
| 0.0693        | 8.0   | 864  | 0.8526          | 0.8333   | 0.8049 |
| 0.0495        | 9.0   | 972  | 0.9813          | 0.8241   | 0.8075 |
| 0.0345        | 10.0  | 1080 | 0.9563          | 0.8320   | 0.8095 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1