readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-small-finer-longer
    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-small-finer-longer
  
  This model is a fine-tuned version of [muhtasham/bert-small-finer](https://huggingface.co/muhtasham/bert-small-finer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4264
  
  ## 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: 64
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | No log        | 0.49  | 500   | 1.6683          |
  | 1.5941        | 0.97  | 1000  | 1.6569          |
  | 1.5941        | 1.46  | 1500  | 1.6436          |
  | 1.5605        | 1.94  | 2000  | 1.6173          |
  | 1.5605        | 2.43  | 2500  | 1.6073          |
  | 1.5297        | 2.91  | 3000  | 1.6001          |
  | 1.5297        | 3.4   | 3500  | 1.5815          |
  | 1.5022        | 3.89  | 4000  | 1.5756          |
  | 1.5022        | 4.37  | 4500  | 1.5568          |
  | 1.4753        | 4.86  | 5000  | 1.5458          |
  | 1.4753        | 5.34  | 5500  | 1.5399          |
  | 1.4537        | 5.83  | 6000  | 1.5273          |
  | 1.4537        | 6.32  | 6500  | 1.5192          |
  | 1.433         | 6.8   | 7000  | 1.5099          |
  | 1.433         | 7.29  | 7500  | 1.5083          |
  | 1.4169        | 7.77  | 8000  | 1.4957          |
  | 1.4169        | 8.26  | 8500  | 1.4914          |
  | 1.3982        | 8.75  | 9000  | 1.4859          |
  | 1.3982        | 9.23  | 9500  | 1.4697          |
  | 1.3877        | 9.72  | 10000 | 1.4711          |
  | 1.3877        | 10.2  | 10500 | 1.4608          |
  | 1.3729        | 10.69 | 11000 | 1.4583          |
  | 1.3729        | 11.18 | 11500 | 1.4513          |
  | 1.3627        | 11.66 | 12000 | 1.4498          |
  | 1.3627        | 12.15 | 12500 | 1.4396          |
  | 1.357         | 12.63 | 13000 | 1.4415          |
  | 1.357         | 13.12 | 13500 | 1.4347          |
  | 1.3484        | 13.61 | 14000 | 1.4316          |
  | 1.3484        | 14.09 | 14500 | 1.4319          |
  | 1.3442        | 14.58 | 15000 | 1.4268          |
  | 1.3442        | 15.06 | 15500 | 1.4293          |
  | 1.3387        | 15.55 | 16000 | 1.4217          |
  | 1.3387        | 16.03 | 16500 | 1.4241          |
  | 1.3358        | 16.52 | 17000 | 1.4250          |
  | 1.3358        | 17.01 | 17500 | 1.4196          |
  | 1.3344        | 17.49 | 18000 | 1.4193          |
  | 1.3344        | 17.98 | 18500 | 1.4200          |
  | 1.3274        | 18.46 | 19000 | 1.4250          |
  | 1.3274        | 18.95 | 19500 | 1.4168          |
  | 1.3348        | 19.44 | 20000 | 1.4164          |
  | 1.3348        | 19.92 | 20500 | 1.4264          |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  