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results – AI Model by Alviniqnacio | AlphaNeural AI
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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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This model is a fine-tuned version of
distilbert/distilbert-base-uncased-finetuned-sst-2-english
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6240
Accuracy: 0.7872
F1: 0.7875
Precision: 0.7879
Recall: 0.7872
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: 32
eval_batch_size: 32
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
lr_scheduler_warmup_steps: 500
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.6345
0.7599
500
0.6403
0.7393
0.7413
0.7480
0.7393
0.4407
1.5198
1000
0.5656
0.7723
0.7727
0.7747
0.7723
0.2476
2.2796
1500
0.6295
0.7841
0.7843
0.7845
0.7841
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
