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quicky-ai – AI Model by sintaxsaint | AlphaNeural AI
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quicky-ai
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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quicky-ai
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3098
Accuracy: 0.8727
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: 32
seed: 42
distributed_type: tpu
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3063
1.0
4210
0.3110
0.8704
0.2875
2.0
8420
0.3098
0.8727
Framework versions
Transformers 5.0.0
Pytorch 2.9.0+cpu
Datasets 4.8.4
Tokenizers 0.22.2
