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finetuning-sentiment-model-unbalanced-dataset – AI Model by filippoferrari | AlphaNeural AI
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finetuning-sentiment-model-unbalanced-dataset
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model-unbalanced-dataset
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2679
Accuracy: 0.9543
Weighted f1: 0.9541
Micro f1: 0.9543
Macro f1: 0.9398
Weighted recall: 0.9543
Micro recall: 0.9543
Macro recall: 0.9369
Weighted precision: 0.9541
Micro precision: 0.9543
Macro precision: 0.9428
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: 5
Training results
Framework versions
Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2
