readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: SMM-classifier-1
    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. -->
  
  # SMM-classifier-1
  
  This model is a fine-tuned version of [Kuaaangwen/bert-base-cased-finetuned-chemistry](https://huggingface.co/Kuaaangwen/bert-base-cased-finetuned-chemistry) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5506
  - Accuracy: 0.8333
  
  ## 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
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 7    | 0.2044          | 0.8333   |
  | No log        | 2.0   | 14   | 0.3574          | 0.8333   |
  | No log        | 3.0   | 21   | 0.1551          | 0.8333   |
  | No log        | 4.0   | 28   | 0.9122          | 0.8333   |
  | No log        | 5.0   | 35   | 0.9043          | 0.8333   |
  | No log        | 6.0   | 42   | 0.7262          | 0.8333   |
  | No log        | 7.0   | 49   | 0.5977          | 0.8333   |
  | No log        | 8.0   | 56   | 0.5567          | 0.8333   |
  | No log        | 9.0   | 63   | 0.5484          | 0.8333   |
  | No log        | 10.0  | 70   | 0.5506          | 0.8333   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  