squad-bn-qgen-mt5-small-v1 – AI Model by jannatul17 | AlphaNeural AI

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jannatul17/
squad-bn-qgen-mt5-small-v1

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text2text-generation

generated_from_trainer

text-generation-inference

endpoints_compatible

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final-squad-bn-qgen-mt5-small-all-metric-v2

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6559
Rouge1 Precision: 31.143
Rouge1 Recall: 24.8687
Rouge1 Fmeasure: 26.7861
Rouge2 Precision: 12.1721
Rouge2 Recall: 9.3907
Rouge2 Fmeasure: 10.1945
Rougel Precision: 29.2741
Rougel Recall: 23.4105
Rougel Fmeasure: 25.196
Rougelsum Precision: 29.2488
Rougelsum Recall: 23.3873
Rougelsum Fmeasure: 25.1783
Bleu-1: 20.2844
Bleu-2: 11.7083
Bleu-3: 7.2251
Bleu-4: 4.6646
Meteor: 0.1144

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: 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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1 Precision	Rouge1 Recall	Rouge1 Fmeasure	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure	Rougel Precision	Rougel Recall	Rougel Fmeasure	Rougelsum Precision	Rougelsum Recall	Rougelsum Fmeasure	Bleu-1	Bleu-2	Bleu-3	Bleu-4	Meteor
0.9251	1.0	6769	0.7237	26.4973	20.6282	22.3983	9.3138	6.9928	7.6534	24.9538	19.4635	21.1113	24.9713	19.4608	21.119	17.5414	9.5172	5.6104	3.4646	0.097
0.8214	2.0	13538	0.6804	29.524	23.4125	25.2574	11.2954	8.6345	9.3841	27.8173	22.1005	23.8164	27.7939	22.0878	23.801	19.2368	10.9056	6.6821	4.2702	0.1074
0.7914	3.0	20307	0.6600	30.7136	24.5527	26.4259	11.8743	9.1634	9.9452	28.8725	23.1161	24.859	28.8566	23.1018	24.8457	19.9315	11.4473	7.0613	4.5701	0.1119
0.7895	4.0	27076	0.6559	31.1568	24.8787	26.8004	12.1685	9.3879	10.1929	29.2804	23.3999	25.1925	29.2554	23.3891	25.1818	20.2844	11.7083	7.2251	4.6646	0.1144

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1