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t5-base-billsum_model – AI Model by alaahussein | AlphaNeural AI
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t5-base-billsum_model
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transformers
pytorch
tensorboard
t5
text2text-generation
generated_from_trainer
billsum
apache-2.0
text-generation-inference
endpoints_compatible
us
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t5-base-billsum_model
This model is a fine-tuned version of
t5-base
on the billsum dataset. It achieves the following results on the evaluation set:
eval_loss: 1.3212
eval_rouge1: 0.2449
eval_rouge2: 0.199
eval_rougeL: 0.2377
eval_rougeLsum: 0.2377
eval_gen_len: 18.9997
eval_bleu: 0.0019
eval_runtime: 199.0696
eval_samples_per_second: 16.421
eval_steps_per_second: 1.03
epoch: 9.0
step: 2666
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
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 40
mixed_precision_training: Native AMP
Framework versions
Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
