t5-small_qa_no_context-finetuned-xsum

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

• Loss: 1.9746
• Rouge1: 19.7961
• Rouge2: 10.0489
• Rougel: 19.2238
• Rougelsum: 19.2447
• Gen Len: 30.4007
• Bleu: 0.1028
• Precisions: [0.3009342079109521, 0.16163349347975292, 0.09752972164875062, 0.05952380952380952]
• Brevity Penalty: 0.7931
• Length Ratio: 0.8118
• Translation Length: 15093
• Reference Length: 18591

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: 64
• eval_batch_size: 64
• 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: 100
• 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