Summarization – AI Model by mzizo4110 | AlphaNeural AI

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mzizo4110/
Summarization

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abisee/cnn_dailymail

google-t5/t5-small

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Summarization

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1039

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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

Training Loss	Epoch	Step	Validation Loss
5.362	0.2229	500	1.4059
1.3409	0.4458	1000	1.1536
1.1552	0.6687	1500	1.1228
1.1308	0.8916	2000	1.1134
1.1192	1.1141	2500	1.1088
1.1165	1.3370	3000	1.1061
1.1147	1.5599	3500	1.1046
1.1151	1.7828	4000	1.1039

Framework versions

PEFT 0.14.0
Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0