--- 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-5-maxep-20 results: [] --- # t5-abs-2309-1054-lr-0.0001-bs-5-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: 4.0305 - Rouge/rouge1: 0.4716 - Rouge/rouge2: 0.2252 - Rouge/rougel: 0.4006 - Rouge/rougelsum: 0.402 - Bertscore/bertscore-precision: 0.8972 - Bertscore/bertscore-recall: 0.8983 - Bertscore/bertscore-f1: 0.8976 - Meteor: 0.4354 - Gen Len: 41.2455 ## 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: 5 - eval_batch_size: 5 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 10 - 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 | |:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:| | 0.0239 | 1.0 | 87 | 3.5307 | 0.4777 | 0.229 | 0.409 | 0.4106 | 0.8977 | 0.8993 | 0.8984 | 0.4382 | 41.0545 | | 0.0141 | 2.0 | 174 | 3.6667 | 0.4765 | 0.2246 | 0.4059 | 0.4075 | 0.9001 | 0.8985 | 0.8991 | 0.429 | 39.2364 | | 0.027 | 3.0 | 261 | 3.7158 | 0.4704 | 0.219 | 0.3992 | 0.3991 | 0.8956 | 0.8967 | 0.896 | 0.4319 | 40.8455 | | 0.0247 | 4.0 | 348 | 3.7320 | 0.4663 | 0.2173 | 0.3945 | 0.3947 | 0.8959 | 0.8973 | 0.8965 | 0.4271 | 41.6 | | 0.0225 | 5.0 | 435 | 3.8031 | 0.4767 | 0.2219 | 0.4017 | 0.4025 | 0.8975 | 0.8977 | 0.8975 | 0.4341 | 40.1 | | 0.0196 | 6.0 | 522 | 3.8516 | 0.4703 | 0.2223 | 0.3989 | 0.3996 | 0.8958 | 0.8977 | 0.8967 | 0.4337 | 41.4 | | 0.0168 | 7.0 | 609 | 3.9028 | 0.4747 | 0.227 | 0.4023 | 0.4029 | 0.8968 | 0.8987 | 0.8976 | 0.4378 | 41.3 | | 0.0165 | 8.0 | 696 | 3.9116 | 0.4676 | 0.2224 | 0.3955 | 0.397 | 0.8965 | 0.8974 | 0.8968 | 0.4305 | 41.4727 | | 0.0153 | 9.0 | 783 | 3.9268 | 0.4737 | 0.2288 | 0.4016 | 0.4025 | 0.8965 | 0.8984 | 0.8973 | 0.4411 | 41.4545 | | 0.0149 | 10.0 | 870 | 3.9513 | 0.48 | 0.2329 | 0.4095 | 0.4101 | 0.8989 | 0.8997 | 0.8992 | 0.4438 | 41.0273 | | 0.0142 | 11.0 | 957 | 3.9677 | 0.475 | 0.226 | 0.4037 | 0.4043 | 0.8949 | 0.8987 | 0.8967 | 0.4474 | 42.6182 | | 0.0132 | 12.0 | 1044 | 3.9769 | 0.4703 | 0.2243 | 0.3977 | 0.3986 | 0.8967 | 0.8977 | 0.8971 | 0.4359 | 41.0182 | | 0.0128 | 13.0 | 1131 | 3.9994 | 0.4695 | 0.2232 | 0.3987 | 0.3996 | 0.8958 | 0.8983 | 0.8969 | 0.4401 | 42.0545 | | 0.012 | 14.0 | 1218 | 4.0018 | 0.471 | 0.2252 | 0.3992 | 0.3991 | 0.8963 | 0.8989 | 0.8975 | 0.4397 | 41.8909 | | 0.0104 | 15.0 | 1305 | 4.0231 | 0.4799 | 0.2297 | 0.4066 | 0.4076 | 0.8975 | 0.8995 | 0.8984 | 0.446 | 41.6091 | | 0.0104 | 16.0 | 1392 | 4.0239 | 0.4758 | 0.2309 | 0.4057 | 0.4059 | 0.8982 | 0.8994 | 0.8987 | 0.4439 | 41.3636 | | 0.0094 | 17.0 | 1479 | 4.0272 | 0.4752 | 0.2275 | 0.4035 | 0.4045 | 0.8977 | 0.8991 | 0.8983 | 0.4404 | 41.6455 | | 0.0093 | 18.0 | 1566 | 4.0272 | 0.4736 | 0.2264 | 0.4026 | 0.4036 | 0.8973 | 0.8988 | 0.8979 | 0.4394 | 41.7545 | | 0.0098 | 19.0 | 1653 | 4.0307 | 0.4736 | 0.2258 | 0.4018 | 0.403 | 0.8971 | 0.8984 | 0.8976 | 0.4362 | 41.1455 | | 0.0084 | 20.0 | 1740 | 4.0305 | 0.4716 | 0.2252 | 0.4006 | 0.402 | 0.8972 | 0.8983 | 0.8976 | 0.4354 | 41.2455 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1