readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: domlm-finetuned-cleaneval
    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. -->
  
  # domlm-finetuned-cleaneval
  
  This model is a fine-tuned version of [albertus-casm/dom-lm-epoch-3](https://huggingface.co/albertus-casm/dom-lm-epoch-3) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2098
  - Precision: 0.9438
  - Recall: 0.9559
  - F1: 0.9498
  - Accuracy: 0.9412
  
  ## 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: 0.0002
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 111  | 0.2472          | 0.9163    | 0.9636 | 0.9394 | 0.9276   |
  | No log        | 2.0   | 222  | 0.1798          | 0.9313    | 0.9671 | 0.9489 | 0.9393   |
  | No log        | 3.0   | 333  | 0.2098          | 0.9438    | 0.9559 | 0.9498 | 0.9412   |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.1.dev0
  - Tokenizers 0.12.1
  