readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: toxicBERT-params
    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
  
  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: 0.2938
  - Precision: 0.0
  - Recall: 0.0
  - F1: 0.0
  - Accuracy: 0.9174
  
  ## 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: 16
  - 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: 0.1
  - num_epochs: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
  | No log        | 1.0   | 174  | 0.2364          | 0.0       | 0.0    | 0.0 | 0.9077   |
  | No log        | 2.0   | 348  | 0.2113          | 0.0       | 0.0    | 0.0 | 0.9190   |
  | 0.2654        | 3.0   | 522  | 0.2195          | 0.0       | 0.0    | 0.0 | 0.9223   |
  | 0.2654        | 4.0   | 696  | 0.2401          | 0.0       | 0.0    | 0.0 | 0.9211   |
  | 0.2654        | 5.0   | 870  | 0.2679          | 0.0       | 0.0    | 0.0 | 0.9198   |
  | 0.0844        | 6.0   | 1044 | 0.2930          | 0.0       | 0.0    | 0.0 | 0.9138   |
  | 0.0844        | 7.0   | 1218 | 0.2938          | 0.0       | 0.0    | 0.0 | 0.9174   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  