--- license: apache-2.0 base_model: google/t5-v1_1-large tags: - generated_from_trainer model-index: - name: SBIC-google-t5-v1_1-large-inter_model-dataset-frequency-human_annots_str results: [] --- # SBIC-google-t5-v1_1-large-inter_model-dataset-frequency-human_annots_str This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## 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: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | 7.5892 | 1.0 | 392 | 8.1616 | | 0.6051 | 2.0 | 784 | 0.4203 | | 0.4096 | 3.0 | 1176 | 0.3717 | | 0.4094 | 4.0 | 1568 | 0.3578 | | 0.3419 | 5.0 | 1960 | 0.3266 | | 0.3587 | 6.0 | 2352 | 0.3206 | | 0.3431 | 7.0 | 2744 | 0.3057 | | 0.355 | 8.0 | 3136 | 0.3103 | | 0.3327 | 9.0 | 3528 | 0.3023 | | 0.3089 | 10.0 | 3920 | 0.2948 | | 0.2803 | 11.0 | 4312 | 0.3010 | | 0.3204 | 12.0 | 4704 | 0.2951 | | 0.3148 | 13.0 | 5096 | 0.2864 | | 0.2896 | 14.0 | 5488 | 0.2830 | | 0.3081 | 15.0 | 5880 | 0.2825 | | 0.3012 | 16.0 | 6272 | 0.2808 | | 0.2788 | 17.0 | 6664 | 0.2814 | | 0.288 | 18.0 | 7056 | 0.2770 | | 0.2648 | 19.0 | 7448 | 0.2697 | | 0.3098 | 20.0 | 7840 | 0.2662 | | 0.2592 | 21.0 | 8232 | 0.2651 | | 0.2394 | 22.0 | 8624 | 0.2675 | | 0.2716 | 23.0 | 9016 | 0.2617 | | 0.2684 | 24.0 | 9408 | 0.2638 | | 0.2729 | 25.0 | 9800 | 0.2627 | | 0.2896 | 26.0 | 10192 | 0.2625 | | 0.2652 | 27.0 | 10584 | 0.2625 | | 0.2611 | 28.0 | 10976 | 0.2625 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.14.5 - Tokenizers 0.14.1