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colab-1k-samples-classifier – AI Model by Sonikatvs18 | AlphaNeural AI
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colab-1k-samples-classifier
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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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colab-1k-samples-classifier
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: 0.7029
Accuracy: 0.4
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: Use OptimizerNames.ADAMW_TORCH_FUSED 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
0.6949
1.0
50
0.6924
0.5
0.6951
2.0
100
0.6919
0.55
0.6809
3.0
150
0.6933
0.53
Framework versions
Transformers 5.10.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
