readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-uncased-finetuned-removed-0530
    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-base-uncased-finetuned-removed-0530
  
  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: 1.1269
  - Accuracy: 0.8745
  - F1: 0.8745
  
  ## 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: 8
  - 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_steps: 1000
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 3180  | 0.5939          | 0.8113   | 0.8113 |
  | No log        | 2.0   | 6360  | 0.6459          | 0.8189   | 0.8183 |
  | No log        | 3.0   | 9540  | 0.6523          | 0.8597   | 0.8604 |
  | No log        | 4.0   | 12720 | 0.8159          | 0.8522   | 0.8521 |
  | No log        | 5.0   | 15900 | 0.9294          | 0.8601   | 0.8599 |
  | No log        | 6.0   | 19080 | 1.0066          | 0.8594   | 0.8592 |
  | No log        | 7.0   | 22260 | 1.0268          | 0.8686   | 0.8689 |
  | 0.2451        | 8.0   | 25440 | 1.0274          | 0.8758   | 0.8760 |
  | 0.2451        | 9.0   | 28620 | 1.0850          | 0.8726   | 0.8727 |
  | 0.2451        | 10.0  | 31800 | 1.1269          | 0.8745   | 0.8745 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.0
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  