--- license: apache-2.0 base_model: google/mt5-small tags: - generated_from_trainer metrics: - accuracy model-index: - name: mt5-small-task3-dataset1 results: [] --- # mt5-small-task3-dataset1 This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3592 - Accuracy: 0.14 ## 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: 5.6e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 12 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.6139 | 1.0 | 250 | 1.3916 | 0.102 | | 1.5289 | 2.0 | 500 | 1.4550 | 0.108 | | 1.4823 | 3.0 | 750 | 1.3630 | 0.132 | | 1.4372 | 4.0 | 1000 | 1.3930 | 0.116 | | 1.4563 | 5.0 | 1250 | 1.3857 | 0.124 | | 1.4347 | 6.0 | 1500 | 1.3708 | 0.124 | | 1.4303 | 7.0 | 1750 | 1.3856 | 0.136 | | 1.4072 | 8.0 | 2000 | 1.3595 | 0.136 | | 1.4045 | 9.0 | 2250 | 1.3677 | 0.13 | | 1.3861 | 10.0 | 2500 | 1.3511 | 0.13 | | 1.376 | 11.0 | 2750 | 1.3543 | 0.136 | | 1.3699 | 12.0 | 3000 | 1.3592 | 0.14 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0