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finetuning-sentiment-model-1900-samples-6-labels – AI Model by rezaFarsh | AlphaNeural AI
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finetuning-sentiment-model-1900-samples-6-labels
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transformers
pytorch
bert
text-classification
generated_from_trainer
google-bert/bert-base-multilingual-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model-1900-samples-6-labels
This model is a fine-tuned version of
bert-base-multilingual-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.1934
Accuracy: 0.6667
F1 Score: 0.6574
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: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Framework versions
Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.0
