readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
    name: bert-base-uncased-finetuned-semeval2020-task4a-append-e2-b32-l5e5
  ---
  
  <!-- 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-semeval2020-task4a-append-e2-b32-l5e5
  
  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: 0.5466
  - Accuracy: 0.8890
  
  ## 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: 4e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 344  | 0.3057          | 0.8630   |
  | 0.4091        | 2.0   | 688  | 0.2964          | 0.8880   |
  | 0.1322        | 3.0   | 1032 | 0.4465          | 0.8820   |
  | 0.1322        | 4.0   | 1376 | 0.5466          | 0.8890   |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.1
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  