--- license: mit tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: roberta-base-finetuned-3d-sentiment results: [] --- # roberta-base-finetuned-3d-sentiment 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: 0.5817 - Accuracy: 0.7753 - Precision: 0.7757 - Recall: 0.7753 - F1: 0.7745 ## 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: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 6381 - num_epochs: 7 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.7758 | 1.0 | 1595 | 0.7691 | 0.7069 | 0.7256 | 0.7069 | 0.7052 | | 0.5496 | 2.0 | 3190 | 0.6961 | 0.7255 | 0.7441 | 0.7255 | 0.7252 | | 0.4856 | 3.0 | 4785 | 0.6451 | 0.7368 | 0.7562 | 0.7368 | 0.7328 | | 0.4257 | 4.0 | 6380 | 0.5817 | 0.7753 | 0.7757 | 0.7753 | 0.7745 | | 0.351 | 5.0 | 7975 | 0.6637 | 0.7633 | 0.7717 | 0.7633 | 0.7637 | | 0.2551 | 6.0 | 9570 | 0.7646 | 0.7696 | 0.7738 | 0.7696 | 0.7699 | | 0.1845 | 7.0 | 11165 | 0.8529 | 0.7674 | 0.7730 | 0.7674 | 0.7680 | ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cu117 - Datasets 2.10.1 - Tokenizers 0.13.3