readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: label-transfer
    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. -->
  
  # label-transfer
  
  This model is a fine-tuned version of [saattrupdan/verdict-classifier](https://huggingface.co/saattrupdan/verdict-classifier) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0452
  - F1 Macro: 0.9872
  - F1 Misinformation: 0.9918
  - F1 Factual: 0.9979
  - F1 Other: 0.9720
  - Prec Macro: 0.9842
  - Prec Misinformation: 0.9958
  - Prec Factual: 0.9979
  - Prec Other: 0.9588
  
  ## 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
  - gradient_accumulation_steps: 32
  - total_train_batch_size: 2048
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1423
  - num_epochs: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
  | 0.4236        | 0.9   | 5    | 0.4070          | 0.8866   | 0.9477            | 0.9658     | 0.7463   | 0.9306     | 0.9075              | 0.9766       | 0.9077     |
  | 0.4175        | 1.9   | 10   | 0.4001          | 0.8872   | 0.9480            | 0.9658     | 0.7477   | 0.9308     | 0.9079              | 0.9766       | 0.9080     |
  | 0.4115        | 2.9   | 15   | 0.3884          | 0.8896   | 0.9487            | 0.9668     | 0.7534   | 0.9323     | 0.9093              | 0.9787       | 0.9090     |
  | 0.3932        | 3.9   | 20   | 0.3719          | 0.8943   | 0.9509            | 0.9668     | 0.7652   | 0.9343     | 0.9133              | 0.9787       | 0.9110     |
  | 0.3785        | 4.9   | 25   | 0.3505          | 0.8973   | 0.9522            | 0.9668     | 0.7730   | 0.9353     | 0.9160              | 0.9787       | 0.9112     |
  | 0.3653        | 5.9   | 30   | 0.3266          | 0.9009   | 0.9535            | 0.9683     | 0.7809   | 0.9369     | 0.9186              | 0.9818       | 0.9104     |
  | 0.3337        | 6.9   | 35   | 0.3028          | 0.9143   | 0.9599            | 0.9694     | 0.8137   | 0.9425     | 0.9310              | 0.9818       | 0.9148     |
  | 0.3181        | 7.9   | 40   | 0.2796          | 0.9181   | 0.9624            | 0.9673     | 0.8245   | 0.9431     | 0.9361              | 0.9807       | 0.9125     |
  | 0.2976        | 8.9   | 45   | 0.2570          | 0.9199   | 0.9633            | 0.9673     | 0.8291   | 0.9434     | 0.9383              | 0.9807       | 0.9113     |
  | 0.2845        | 9.9   | 50   | 0.2349          | 0.9242   | 0.9658            | 0.9668     | 0.8401   | 0.9453     | 0.9430              | 0.9797       | 0.9131     |
  | 0.2649        | 10.9  | 55   | 0.2134          | 0.9270   | 0.9673            | 0.9668     | 0.8470   | 0.9451     | 0.9472              | 0.9797       | 0.9086     |
  | 0.2399        | 11.9  | 60   | 0.1929          | 0.9330   | 0.9704            | 0.9668     | 0.8619   | 0.9467     | 0.9547              | 0.9797       | 0.9057     |
  | 0.224         | 12.9  | 65   | 0.1735          | 0.9369   | 0.9724            | 0.9673     | 0.8710   | 0.9467     | 0.9608              | 0.9797       | 0.8996     |
  | 0.1992        | 13.9  | 70   | 0.1564          | 0.9496   | 0.9783            | 0.9711     | 0.8995   | 0.9531     | 0.9744              | 0.9809       | 0.9039     |
  | 0.1908        | 14.9  | 75   | 0.1427          | 0.9501   | 0.9784            | 0.9711     | 0.9006   | 0.9519     | 0.9765              | 0.9799       | 0.8993     |
  | 0.1785        | 15.9  | 80   | 0.1309          | 0.9542   | 0.9790            | 0.9765     | 0.9072   | 0.9549     | 0.9782              | 0.9791       | 0.9076     |
  | 0.1637        | 16.9  | 85   | 0.1215          | 0.9531   | 0.9791            | 0.9745     | 0.9056   | 0.9536     | 0.9784              | 0.9750       | 0.9073     |
  | 0.151         | 17.9  | 90   | 0.1131          | 0.9540   | 0.9787            | 0.9771     | 0.9064   | 0.9549     | 0.9776              | 0.9771       | 0.9099     |
  | 0.1395        | 18.9  | 95   | 0.1049          | 0.9555   | 0.9790            | 0.9787     | 0.9088   | 0.9558     | 0.9784              | 0.9772       | 0.9119     |
  | 0.1285        | 19.9  | 100  | 0.0963          | 0.9600   | 0.9799            | 0.9833     | 0.9169   | 0.9602     | 0.9798              | 0.9843       | 0.916