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%