readme: ---
  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
  