POCTS – AI Model by jogonba2 | AlphaNeural AI

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jogonba2/
POCTS

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text2text-generation

endpoints_compatible

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POCTS

This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.0970
Rouge1: 26.1391
Rouge2: 7.3101
Rougel: 19.1217
Rougelsum: 21.9706
Gen Len: 46.2245

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.15
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.3259	1.0	33875	3.2535	17.942	4.5143	14.2766	15.582	19.3901
2.9764	2.0	67750	3.1278	18.6558	5.1844	15.0939	16.3367	19.9174
2.5889	3.0	101625	3.0970	19.1763	5.4517	15.5342	16.7186	19.8855

Framework versions

Transformers 4.10.2
Pytorch 1.7.1+cu110
Datasets 1.11.0
Tokenizers 0.10.3