--- tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: MLMA_GPT_Lab8_custom_trained results: [] --- # MLMA_GPT_Lab8_custom_trained This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1406 - Precision: 0.5275 - Recall: 0.5723 - F1: 0.5490 - Accuracy: 0.9563 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 474 | 0.1706 | 0.4389 | 0.3693 | 0.4011 | 0.9452 | | 0.2264 | 2.0 | 948 | 0.1624 | 0.4957 | 0.5850 | 0.5367 | 0.9495 | | 0.1305 | 3.0 | 1422 | 0.1406 | 0.5275 | 0.5723 | 0.5490 | 0.9563 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2