T5-small_finetuned_billsum_subset_model_bs32_lr2e-05

This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:

• Loss: 1.9763
• Rouge1: 0.1887
• Rouge2: 0.0967
• Rougel: 0.1659
• Rougelsum: 0.1657
• Gen Len: 19.0
• Bleu: 0.0008

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: 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: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len	Bleu
No log	1.0	31	1.9837	0.1873	0.0945	0.1635	0.1633	19.0	0.0007
No log	2.0	62	1.9812	0.1884	0.0955	0.1652	0.1648	19.0	0.0007
No log	3.0	93	1.9785	0.1866	0.0936	0.1636	0.1634	19.0	0.0007
No log	4.0	124	1.9763	0.1887	0.0967	0.1659	0.1657	19.0	0.0008

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3