inshorts-news-summary – AI Model by sandeep16064 | AlphaNeural AI

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sandeep16064/
inshorts-news-summary

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text2text-generation

abstractive summarization

sandeep16064/news_summary

google/mt5-small

endpoints_compatible

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mt5-small-finetuned-inshorts-news-summary

This model is a fine-tuned version of google/mt5-small on the [inshorts-news-summary dataset] (https://huggingface.co/datasets/sandeep16064/news_summary). It achieves the following results on the evaluation set:

Loss: 1.5399
Rouge1: 54.613
Rouge2: 31.1543
Rougel: 50.7709
Rougelsum: 50.7907

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: 5.6e-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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.3244	1.0	5511	1.8904	51.0778	28.3112	47.4136	47.404
2.2747	2.0	11022	1.7450	51.8372	28.9814	48.0917	48.0965
2.0745	3.0	16533	1.6567	52.518	29.7276	48.727	48.7504
1.9516	4.0	22044	1.6210	54.2404	30.8927	50.4042	50.3996
1.8714	5.0	27555	1.5971	53.8556	30.6665	50.112	50.1177
1.8112	6.0	33066	1.5649	54.179	31.0178	50.407	50.4281
1.7644	7.0	38577	1.5605	54.3104	30.7997	50.4555	50.4861
1.7265	8.0	44088	1.5447	54.5593	31.0283	50.6343	50.6605
1.7013	9.0	49599	1.5440	54.7385	31.3073	50.9111	50.9334
1.6864	10.0	55110	1.5399	54.613	31.1543	50.7709	50.7907

Framework versions

Transformers 4.32.1
Pytorch 2.1.0
Datasets 2.12.0
Tokenizers 0.13.3