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financial_text_sentiment_classification_model – AI Model by Abhra-loony | AlphaNeural AI
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Abhra-loony
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financial_text_sentiment_classification_model
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tf
roberta
generated_from_keras_callback
FacebookAI/roberta-base
finetune
mit
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Abhra-loony/financial_text_sentiment_classification_model
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4016
Validation Loss: 0.4311
Train Accuracy: 0.7930
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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-06, 'decay_steps': 1460, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Accuracy
Epoch
0.9596
0.8704
0.5449
0
0.7972
0.7030
0.6689
1
0.5561
0.4668
0.7921
2
0.4376
0.4376
0.7904
3
0.4016
0.4311
0.7930
4
Framework versions
Transformers 4.42.4
TensorFlow 2.17.0
Datasets 2.21.0
Tokenizers 0.19.1
