--- license: mit base_model: roberta-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: BLESSRelationTrain-2 results: [] --- # BLESSRelationTrain-2 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6280 - Accuracy: 0.8473 ## 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: 5e-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: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 0.8 | 100 | 0.6965 | 0.5 | | No log | 1.6 | 200 | 0.6828 | 0.5868 | | No log | 2.4 | 300 | 0.7161 | 0.5 | | No log | 3.2 | 400 | 0.6493 | 0.6377 | | 0.6926 | 4.0 | 500 | 0.6856 | 0.5269 | | 0.6926 | 4.8 | 600 | 0.6096 | 0.7784 | | 0.6926 | 5.6 | 700 | 0.6265 | 0.8204 | | 0.6926 | 6.4 | 800 | 0.8188 | 0.8054 | | 0.6926 | 7.2 | 900 | 0.5995 | 0.8503 | | 0.3811 | 8.0 | 1000 | 0.6280 | 0.8473 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.14.5 - Tokenizers 0.14.1