t5-large_qa_no_context-finetuned-xsum

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

• Loss: nan
• Rouge1: 3.1495
• Rouge2: 1.4179
• Rougel: 2.6574
• Rougelsum: 2.6307
• Gen Len: 14.5753
• Bleu: 0.0043
• Precisions: [0.08109897384971863, 0.030190884300740163, 0.02365744026496333, 0.023673958645489962]
• Brevity Penalty: 0.1252
• Length Ratio: 0.3249
• Translation Length: 6042
• 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: 32
• eval_batch_size: 32
• 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: 10
• 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