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xlm-roberta-large-finetuned-ac_v3 – AI Model by mafaisalsust | AlphaNeural AI
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mafaisalsust
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xlm-roberta-large-finetuned-ac_v3
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transformers
tf
xlm-roberta
fill-mask
generated_from_keras_callback
mit
autotrain_compatible
endpoints_compatible
us
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mafaisalsust/xlm-roberta-large-finetuned-ac_v3
This model is a fine-tuned version of
xlm-roberta-large
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 2.1278
Validation Loss: 1.9549
Epoch: 4
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': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 406, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '
passive_serialization
': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
4.8685
1.9501
0
2.1307
1.9643
1
2.1332
1.9703
2
2.1289
1.9530
3
2.1278
1.9549
4
Framework versions
Transformers 4.26.1
TensorFlow 2.8.0
Datasets 2.10.1
Tokenizers 0.13.2
