--- license: mit base_model: facebook/esm2_t12_35M_UR50D tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: esm2_t12_35M_UR50D-finetuned-SO2F results: [] --- # esm2_t12_35M_UR50D-finetuned-SO2F This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6688 - Accuracy: 0.6211 - Precision: 0.1405 - Recall: 0.5863 - F1: 0.2267 - Auc: 0.6055 - Mcc: 0.1264 ## 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: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - 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 | Accuracy | Precision | Recall | F1 | Auc | Mcc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:------:| | No log | 1.0 | 108 | 0.6805 | 0.5162 | 0.1158 | 0.6192 | 0.1952 | 0.5623 | 0.0730 | | No log | 2.0 | 216 | 0.6716 | 0.5824 | 0.1306 | 0.6027 | 0.2147 | 0.5915 | 0.1080 | | No log | 3.0 | 324 | 0.6688 | 0.6211 | 0.1405 | 0.5863 | 0.2267 | 0.6055 | 0.1264 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2