readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: testc8-1
    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. -->
  
  # testc8-1
  
  This model is a fine-tuned version of [shafin/chemical-bert-uncased-finetuned-cust-c2](https://huggingface.co/shafin/chemical-bert-uncased-finetuned-cust-c2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1490
  
  ## 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: 2e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.0415        | 1.0   | 16   | 0.1392          |
  | 0.0443        | 2.0   | 32   | 0.1289          |
  | 0.0471        | 3.0   | 48   | 0.1363          |
  | 0.042         | 4.0   | 64   | 0.1598          |
  | 0.0452        | 5.0   | 80   | 0.1571          |
  | 0.0446        | 6.0   | 96   | 0.1733          |
  | 0.0466        | 7.0   | 112  | 0.1301          |
  | 0.0391        | 8.0   | 128  | 0.1359          |
  | 0.0425        | 9.0   | 144  | 0.1324          |
  | 0.0436        | 10.0  | 160  | 0.0939          |
  | 0.0406        | 11.0  | 176  | 0.1495          |
  | 0.0387        | 12.0  | 192  | 0.1592          |
  | 0.0335        | 13.0  | 208  | 0.1118          |
  | 0.0413        | 14.0  | 224  | 0.1508          |
  | 0.0363        | 15.0  | 240  | 0.1471          |
  | 0.0428        | 16.0  | 256  | 0.1721          |
  | 0.0384        | 17.0  | 272  | 0.1853          |
  | 0.0381        | 18.0  | 288  | 0.1578          |
  | 0.0373        | 19.0  | 304  | 0.1707          |
  | 0.0351        | 20.0  | 320  | 0.1241          |
  | 0.0346        | 21.0  | 336  | 0.1602          |
  | 0.0386        | 22.0  | 352  | 0.1207          |
  | 0.0274        | 23.0  | 368  | 0.1642          |
  | 0.0338        | 24.0  | 384  | 0.1169          |
  | 0.0327        | 25.0  | 400  | 0.1461          |
  | 0.026         | 26.0  | 416  | 0.1323          |
  | 0.0315        | 27.0  | 432  | 0.1403          |
  | 0.042         | 28.0  | 448  | 0.1056          |
  | 0.0346        | 29.0  | 464  | 0.1186          |
  | 0.0294        | 30.0  | 480  | 0.1490          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  