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t5-finetuned-xsum – AI Model by zayzay234 | AlphaNeural AI
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t5-finetuned-xsum
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transformers
tensorboard
safetensors
t5
text2text-generation
generated_from_trainer
xsum
text-generation-inference
endpoints_compatible
us
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t5-finetuned-xsum
This model was trained from scratch on the xsum dataset. It achieves the following results on the evaluation set:
eval_loss: 2.4495
eval_model_preparation_time: 0.0166
eval_rouge1: 28.922
eval_rouge2: 8.0792
eval_rougeL: 22.7364
eval_rougeLsum: 22.7374
eval_gen_len: 19.7064
eval_runtime: 904.3584
eval_samples_per_second: 12.53
eval_steps_per_second: 1.567
step: 0
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1
