--- license: apache-2.0 base_model: google-t5/t5-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: t5_es_farshad_half_4_4 results: [] --- # t5_es_farshad_half_4_4 This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0424 - Accuracy: 0.9922 - F1: 0.9924 ## 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: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 64 - total_train_batch_size: 4096 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| | 0.7459 | 5.8501 | 50 | 0.6868 | 0.5426 | 0.6423 | | 0.6483 | 11.7002 | 100 | 0.5144 | 0.8518 | 0.8540 | | 0.3069 | 17.5503 | 150 | 0.1038 | 0.9675 | 0.9681 | | 0.0869 | 23.4004 | 200 | 0.0563 | 0.9820 | 0.9825 | | 0.0496 | 29.2505 | 250 | 0.0440 | 0.9864 | 0.9868 | | 0.0327 | 35.1005 | 300 | 0.0365 | 0.9887 | 0.9891 | | 0.0226 | 40.9506 | 350 | 0.0333 | 0.9916 | 0.9919 | | 0.0161 | 46.8007 | 400 | 0.0316 | 0.9925 | 0.9927 | | 0.0125 | 52.6508 | 450 | 0.0311 | 0.9936 | 0.9938 | | 0.0097 | 58.5009 | 500 | 0.0322 | 0.9933 | 0.9935 | | 0.0076 | 64.3510 | 550 | 0.0366 | 0.9927 | 0.9930 | | 0.0069 | 70.2011 | 600 | 0.0407 | 0.9919 | 0.9921 | | 0.0055 | 76.0512 | 650 | 0.0342 | 0.9927 | 0.9930 | | 0.0041 | 81.9013 | 700 | 0.0364 | 0.9936 | 0.9938 | | 0.003 | 87.7514 | 750 | 0.0411 | 0.9933 | 0.9936 | | 0.0026 | 93.6015 | 800 | 0.0424 | 0.9922 | 0.9924 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.19.1