news-summarization-argilla – AI Model by Sl4nia | AlphaNeural AI | AlphaNeural AI

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Sl4nia/
news-summarization-argilla

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text2text-generation

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text-generation-inference

endpoints_compatible

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news-summarization-argilla

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.6405
Rouge1: 0.2882
Rouge2: 0.0847
Rougel: 0.2411
Rougelsum: 0.2412
Gen Len: 19.0

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	12	4.0721	0.2503	0.0688	0.2149	0.2162	19.0
No log	2.0	24	3.8238	0.269	0.0756	0.2266	0.2281	19.0
No log	3.0	36	3.6874	0.283	0.0846	0.2387	0.2388	19.0
No log	4.0	48	3.6405	0.2882	0.0847	0.2411	0.2412	19.0

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2