my-Hindi_Sentiment_Analysis – AI Model by Sahil01ok | AlphaNeural AI

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Sahil01ok/
my-Hindi_Sentiment_Analysis

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text-classification

generated_from_keras_callback

google-bert/bert-base-multilingual-cased

text-embeddings-inference

endpoints_compatible

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my-Hindi_Sentiment_Analysis

This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.6058
Train Accuracy: 0.7586
Validation Loss: 0.6416
Validation Accuracy: 0.7440
Epoch: 2

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': np.float32(5e-05), 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.9017	0.5874	0.7903	0.6960	0
0.7406	0.6845	0.6415	0.7360	1
0.6058	0.7586	0.6416	0.7440	2

Framework versions

Transformers 4.44.2
TensorFlow 2.19.0
Datasets 4.0.0
Tokenizers 0.19.1