mt5-small-v2-sum-fine-tuned – AI Model by HeshamMamdouh | AlphaNeural AI

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HeshamMamdouh/
mt5-small-v2-sum-fine-tuned

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text2text-generation

generated_from_keras_callback

endpoints_compatible

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mt5-small-v2-sum-fine-tuned

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 8.7918
Validation Loss: 9.1352
Epoch: 29

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:

optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
14.5286	12.5993	0
13.7167	12.7206	1
13.7518	12.4721	2
13.5991	12.0654	3
13.0693	11.5237	4
12.8718	11.5755	5
12.6745	11.3361	6
12.4659	10.6694	7
12.2692	10.0483	8
12.2115	10.5089	9
11.9810	10.3895	10
11.6432	10.1090	11
11.6436	9.4868	12
11.3711	9.9035	13
11.1223	8.9180	14
10.9886	9.3682	15
10.8426	8.9964	16
10.5593	9.2168	17
10.5568	8.9877	18
10.1875	8.8072	19
10.1814	10.3268	20
10.0053	11.1192	21
9.6850	10.9950	22
9.6080	10.7909	23
9.4208	10.9226	24
9.3501	10.1040	25
9.2757	10.1148	26
9.1751	9.9607	27
8.9227	9.1899	28
8.7918	9.1352	29

Framework versions

Transformers 4.30.2
TensorFlow 2.11.0
Datasets 2.13.1
Tokenizers 0.12.1