readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: toxicBERT-params-tryout
    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. -->
  
  # toxicBERT-params-tryout
  
  This model is a fine-tuned version of [unitary/toxic-bert](https://huggingface.co/unitary/toxic-bert) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1804
  - Precision: 0.0
  - Recall: 0.0
  - F1: 0.0
  - Accuracy: 0.9314
  
  ## 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: 2e-05
  - train_batch_size: 128
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.15
  - num_epochs: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
  | No log        | 1.0   | 22   | 0.4522          | 0.0       | 0.0    | 0.0 | 0.8795   |
  | No log        | 2.0   | 44   | 0.2784          | 0.0       | 0.0    | 0.0 | 0.8996   |
  | No log        | 3.0   | 66   | 0.2150          | 0.0       | 0.0    | 0.0 | 0.9219   |
  | No log        | 4.0   | 88   | 0.1888          | 0.0       | 0.0    | 0.0 | 0.9297   |
  | No log        | 5.0   | 110  | 0.1829          | 0.0       | 0.0    | 0.0 | 0.9303   |
  | No log        | 6.0   | 132  | 0.1810          | 0.0       | 0.0    | 0.0 | 0.9305   |
  | No log        | 7.0   | 154  | 0.1804          | 0.0       | 0.0    | 0.0 | 0.9314   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  