t5-base-billsum_model

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

• eval_loss: 1.3212
• eval_rouge1: 0.2449
• eval_rouge2: 0.199
• eval_rougeL: 0.2377
• eval_rougeLsum: 0.2377
• eval_gen_len: 18.9997
• eval_bleu: 0.0019
• eval_runtime: 199.0696
• eval_samples_per_second: 16.421
• eval_steps_per_second: 1.03
• epoch: 9.0
• step: 2666

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
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 40
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3