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finetuning-sentiment-model-bert-multilingual – AI Model by coderSounak | AlphaNeural AI
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finetuning-sentiment-model-bert-multilingual
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
cc-by-nc-3.0
autotrain_compatible
endpoints_compatible
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finetuning-sentiment-model-bert-multilingual
This model is a fine-tuned version of
QCRI/bert-base-multilingual-cased-pos-english
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.9412
Accuracy: 0.6624
F1: 0.6624
Precision: 0.6624
Recall: 0.6624
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:
learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
Training results
Framework versions
Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2
