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mt5-small-finedtuned-4-swahili – AI Model by n3wtou | AlphaNeural AI
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n3wtou
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mt5-small-finedtuned-4-swahili
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transformers
tf
mt5
text2text-generation
generated_from_keras_callback
sw
csebuetnlp/xlsum
apache-2.0
endpoints_compatible
us
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n3wtou/mt5-small-finedtuned-4-swahili
This model is a fine-tuned version of
google/mt5-small
on csebuetnlp/xlsum dataset. It achieves the following results on the evaluation set:
Train Loss: 2.4419
Validation Loss: 2.4809
Epoch: 9
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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0003, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 19900, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '
passive_serialization
': True}, 'warmup_steps': 100, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
5.6636
2.9818
0
3.7789
2.7822
1
3.3841
2.6840
2
3.1496
2.6238
3
2.9656
2.5816
4
2.8134
2.5522
5
2.6914
2.5315
6
2.5935
2.4980
7
2.5056
2.4764
8
2.4419
2.4809
9
Framework versions
Transformers 4.30.2
TensorFlow 2.12.0
Datasets 2.12.0
Tokenizers 0.13.3
