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
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Base model
google-t5/t5-3b