t5-base_qa_no_context-finetuned-xsum

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t5-base_qa_no_context-finetuned-xsum

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

• Loss: 1.6412
• Rouge1: 43.3171
• Rouge2: 22.7074
• Rougel: 41.6763
• Rougelsum: 41.7334
• Gen Len: 26.3177
• Bleu: 0.1819
• Precisions: [0.487515762925599, 0.2675321199143469, 0.1598232107214143, 0.10471323978035388]
• Brevity Penalty: 0.8416
• Length Ratio: 0.8529
• Translation Length: 15860
• 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: 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