t5-3b_qa_no_context-finetuned-xsum

This model is a fine-tuned version of google-t5/t5-3b on the None dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Rouge1: 18.7024
• Rouge2: 7.1707
• Rougel: 16.4325
• Rougelsum: 16.1865
• Gen Len: 47.0
• Bleu: 0.0271
• Precisions: [0.1349110901125333, 0.037512295448448536, 0.013424070103477207, 0.007934576254685294]
• Brevity Penalty: 1.0
• Length Ratio: 1.2521
• Translation Length: 23282
• Reference Length: 18595

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu118
• Datasets 3.3.1
• Tokenizers 0.21.0