readme: ---
  license: apache-2.0
  tags:
  - text-classification
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: SPECTER-finetuned-DAGPap22
    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. -->
  
  # SPECTER-finetuned-DAGPap22
  
  This model is a fine-tuned version of [allenai/specter](https://huggingface.co/allenai/specter) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0023
  - Accuracy: 0.9993
  - F1: 0.9995
  
  ## 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: 6e-06
  - 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: 50
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.3422        | 1.0   | 669   | 0.4135          | 0.8914   | 0.9140 |
  | 0.1074        | 2.0   | 1338  | 0.1216          | 0.9746   | 0.9811 |
  | 0.0329        | 3.0   | 2007  | 0.0064          | 0.9989   | 0.9992 |
  | 0.0097        | 4.0   | 2676  | 0.0132          | 0.9972   | 0.9980 |
  | 0.0123        | 5.0   | 3345  | 0.0231          | 0.9961   | 0.9971 |
  | 0.0114        | 6.0   | 4014  | 0.0080          | 0.9985   | 0.9989 |
  | 0.0029        | 7.0   | 4683  | 0.2207          | 0.9727   | 0.9797 |
  | 0.0075        | 8.0   | 5352  | 0.0145          | 0.9974   | 0.9981 |
  | 0.0098        | 9.0   | 6021  | 0.0047          | 0.9994   | 0.9996 |
  | 0.0025        | 10.0  | 6690  | 0.0000          | 1.0      | 1.0    |
  | 0.0044        | 11.0  | 7359  | 0.0035          | 0.9993   | 0.9995 |
  | 0.0           | 12.0  | 8028  | 0.0027          | 0.9996   | 0.9997 |
  | 0.0027        | 13.0  | 8697  | 0.0036          | 0.9993   | 0.9995 |
  | 0.0055        | 14.0  | 9366  | 0.0017          | 0.9998   | 0.9999 |
  | 0.0           | 15.0  | 10035 | 0.0000          | 1.0      | 1.0    |
  | 0.0           | 16.0  | 10704 | 0.0000          | 1.0      | 1.0    |
  | 0.0022        | 17.0  | 11373 | 0.0111          | 0.9981   | 0.9986 |
  | 0.0004        | 18.0  | 12042 | 0.0011          | 0.9994   | 0.9996 |
  | 0.0           | 19.0  | 12711 | 0.0020          | 0.9994   | 0.9996 |
  | 0.0           | 20.0  | 13380 | 0.0023          | 0.9993   | 0.9995 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  