--- license: mit base_model: VietAI/vit5-base tags: - generated_from_trainer metrics: - rouge model-index: - name: mymodel_LORA_base_10k_2e5_3epoch_batch16_T4 results: [] --- # mymodel_LORA_base_10k_2e5_3epoch_batch16_T4 This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.9509 - Rouge1: 0.5087 - Rouge2: 0.21 - Rougel: 0.3279 - Rougelsum: 0.3278 - Gen Len: 47.1885 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | 2.904 | 1.0 | 500 | 2.0384 | 0.4986 | 0.1981 | 0.323 | 0.3231 | 54.0445 | | 2.167 | 2.0 | 1000 | 1.9662 | 0.5068 | 0.2053 | 0.3269 | 0.3268 | 54.8295 | | 2.1217 | 3.0 | 1500 | 1.9509 | 0.5087 | 0.21 | 0.3279 | 0.3278 | 47.1885 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.7 - Tokenizers 0.14.1