t5-small-finetuned-xlsum-with-multi-news-test-5-epoch

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.2989
• Rouge1: 30.8254
• Rouge2: 9.2466
• Rougel: 24.0068
• Rougelsum: 24.0535
• Gen Len: 18.8143

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: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.7346	1.0	20543	2.3901	29.3586	8.2361	22.7798	22.8273	18.8201
2.6739	2.0	41086	2.3414	30.2258	8.77	23.496	23.5405	18.8384
2.6486	3.0	61629	2.3160	30.6221	9.1072	23.8114	23.8584	18.8194
2.648	4.0	82172	2.3033	30.8171	9.2146	23.9993	24.0424	18.8016
2.63	5.0	102715	2.2989	30.8254	9.2466	24.0068	24.0535	18.8143

Framework versions

• Transformers 4.13.0
• Pytorch 1.13.1+cpu
• Datasets 2.8.0
• Tokenizers 0.10.3