t5-v1_1-small-finetuned-summarization-cnn-ver1 – AI Model by Alred | AlphaNeural AI

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t5-v1_1-small-finetuned-summarization-cnn-ver1

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t5-v1_1-small-finetuned-summarization-cnn-ver1

This model is a fine-tuned version of google/t5-v1_1-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

Loss: 2.7467
Bertscore-mean-precision: 0.8764
Bertscore-mean-recall: 0.8519
Bertscore-mean-f1: 0.8639
Bertscore-median-precision: 0.8746
Bertscore-median-recall: 0.8518
Bertscore-median-f1: 0.8632

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: 4e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Bertscore-mean-precision	Bertscore-mean-recall	Bertscore-mean-f1	Bertscore-median-precision	Bertscore-median-recall	Bertscore-median-f1
4.6845	1.0	718	2.9003	0.8698	0.8456	0.8574	0.8693	0.8445	0.8570
3.7925	2.0	1436	2.7654	0.8765	0.8519	0.8639	0.8745	0.8512	0.8629
3.6332	3.0	2154	2.7467	0.8764	0.8519	0.8639	0.8746	0.8518	0.8632

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.0
Tokenizers 0.13.2