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sentiment-model – AI Model by alanbuendiaperez | AlphaNeural AI
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sentiment-model
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased-finetuned-sst-2-english
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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sentiment-model
This model is a fine-tuned version of
distilbert-base-uncased-finetuned-sst-2-english
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3683
Accuracy: 0.9324
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2715
1.0
3125
0.2449
0.9147
0.1485
2.0
6250
0.2800
0.9291
0.0582
3.0
9375
0.3683
0.9324
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
