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Model Card for gena_lm_bert_base_human_classify

Model Details

  • Model Name: gena_lm_bert_base_human_classify
  • Type: Transformer
  • Main Application: [Brief description of the main application of the model, e.g., text classification, image recognition, etc.]

Training Data

  • Description: [Brief description of the training data, including source, nature (text, images, etc.), and size.]
  • Preprocessing: [Details of any preprocessing steps applied to the training data.]

Model Architecture

  • Architecture Details: [Details about the model architecture, e.g., number of layers, type of layers, etc.]
  • Framework Used: PyTorch

Training Procedure

  • Epochs: 2
  • Batch Size: 64
  • Learning Rate: 2e-5
  • Weight Decay: 0.01

Training Performance

  • Epoch 1:

    • Training Loss: 0.088600
    • Validation Loss: 0.079851
    • Accuracy: 96.9529%
    • F1 Score: 96.9840%
    • Precision: 95.7133%
    • Recall: 98.2889%
  • Epoch 2:

    • Training Loss: 0.058800
    • Validation Loss: 0.057442
    • Accuracy: 98.0280%
    • F1 Score: 98.0338%
    • Precision: 97.4486%
    • Recall: 98.6260%