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t5-3b_qa_no_context-finetuned-xsum – AI Model by javedonline | AlphaNeural AI
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t5-3b_qa_no_context-finetuned-xsum
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transformers
safetensors
t5
text2text-generation
generated_from_trainer
google-t5/t5-3b
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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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
