--- license: apache-2.0 base_model: google-t5/t5-base tags: - generated_from_trainer model-index: - name: t5-abs-2309-1054-lr-0.0001-bs-2-maxep-20 results: [] --- # t5-abs-2309-1054-lr-0.0001-bs-2-maxep-20 This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 4.1236 - Rouge/rouge1: 0.4731 - Rouge/rouge2: 0.2208 - Rouge/rougel: 0.3994 - Rouge/rougelsum: 0.4008 - Bertscore/bertscore-precision: 0.8972 - Bertscore/bertscore-recall: 0.897 - Bertscore/bertscore-f1: 0.897 - Meteor: 0.4314 - Gen Len: 40.8273 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge/rouge1 | Rouge/rouge2 | Rouge/rougel | Rouge/rougelsum | Bertscore/bertscore-precision | Bertscore/bertscore-recall | Bertscore/bertscore-f1 | Meteor | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:| | 0.049 | 1.0 | 217 | 3.0726 | 0.4642 | 0.2147 | 0.395 | 0.3945 | 0.8959 | 0.897 | 0.8963 | 0.4246 | 41.0364 | | 0.025 | 2.0 | 434 | 3.5278 | 0.4809 | 0.2331 | 0.4126 | 0.4135 | 0.8997 | 0.9002 | 0.8998 | 0.44 | 40.2545 | | 0.0177 | 3.0 | 651 | 3.7709 | 0.4672 | 0.2131 | 0.3912 | 0.3918 | 0.8974 | 0.8961 | 0.8966 | 0.4224 | 40.0 | | 0.014 | 4.0 | 868 | 3.8327 | 0.4738 | 0.2244 | 0.4005 | 0.4009 | 0.8966 | 0.8985 | 0.8974 | 0.4361 | 42.1364 | | 0.0278 | 5.0 | 1085 | 3.8865 | 0.4679 | 0.2181 | 0.3942 | 0.3949 | 0.8968 | 0.8983 | 0.8974 | 0.4296 | 41.5909 | | 0.0246 | 6.0 | 1302 | 3.8697 | 0.4642 | 0.2147 | 0.3904 | 0.3915 | 0.8959 | 0.8976 | 0.8966 | 0.421 | 41.6818 | | 0.0204 | 7.0 | 1519 | 3.9737 | 0.4646 | 0.2159 | 0.395 | 0.3953 | 0.8964 | 0.8967 | 0.8964 | 0.421 | 40.7273 | | 0.0179 | 8.0 | 1736 | 4.0367 | 0.461 | 0.2102 | 0.3896 | 0.3904 | 0.8969 | 0.8946 | 0.8956 | 0.4122 | 38.9727 | | 0.0158 | 9.0 | 1953 | 4.0384 | 0.4695 | 0.2117 | 0.391 | 0.3921 | 0.8975 | 0.8978 | 0.8976 | 0.4269 | 40.4455 | | 0.0159 | 10.0 | 2170 | 4.0446 | 0.4672 | 0.2166 | 0.3945 | 0.3951 | 0.8966 | 0.8982 | 0.8972 | 0.4296 | 41.3091 | | 0.0126 | 11.0 | 2387 | 4.0704 | 0.4722 | 0.2223 | 0.3966 | 0.3979 | 0.8968 | 0.8978 | 0.8972 | 0.4356 | 41.1636 | | 0.0132 | 12.0 | 2604 | 4.1046 | 0.468 | 0.2207 | 0.4011 | 0.402 | 0.8974 | 0.8978 | 0.8975 | 0.4341 | 40.5636 | | 0.0109 | 13.0 | 2821 | 4.1023 | 0.4743 | 0.2217 | 0.4 | 0.4003 | 0.8978 | 0.8971 | 0.8974 | 0.4311 | 40.6091 | | 0.0106 | 14.0 | 3038 | 4.1477 | 0.4691 | 0.2202 | 0.3979 | 0.3984 | 0.8974 | 0.8963 | 0.8967 | 0.4257 | 40.3545 | | 0.0103 | 15.0 | 3255 | 4.1412 | 0.4753 | 0.2219 | 0.4048 | 0.4063 | 0.8982 | 0.8967 | 0.8973 | 0.4247 | 39.5091 | | 0.01 | 16.0 | 3472 | 4.1251 | 0.4762 | 0.2259 | 0.4045 | 0.4063 | 0.8983 | 0.8978 | 0.898 | 0.4337 | 40.3909 | | 0.0087 | 17.0 | 3689 | 4.1286 | 0.482 | 0.2256 | 0.405 | 0.4063 | 0.8971 | 0.8985 | 0.8976 | 0.4449 | 41.6455 | | 0.0092 | 18.0 | 3906 | 4.1284 | 0.4675 | 0.2185 | 0.3981 | 0.3993 | 0.897 | 0.8973 | 0.897 | 0.4288 | 41.0818 | | 0.0089 | 19.0 | 4123 | 4.1252 | 0.4695 | 0.2182 | 0.3981 | 0.3991 | 0.8966 | 0.897 | 0.8967 | 0.427 | 41.0636 | | 0.0081 | 20.0 | 4340 | 4.1236 | 0.4731 | 0.2208 | 0.3994 | 0.4008 | 0.8972 | 0.897 | 0.897 | 0.4314 | 40.8273 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1