| # 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% |