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idp-headers – AI Model by Anurag0961 | AlphaNeural AI
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idp-headers
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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idp-headers
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: 1.6714
F1: 0.4823
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1
1.7995
1.0
5
1.8557
0.1629
1.7125
2.0
10
1.7832
0.1759
1.6381
3.0
15
1.7243
0.4698
1.5746
4.0
20
1.6857
0.4823
1.5354
5.0
25
1.6714
0.4823
Framework versions
Transformers 4.21.3
Pytorch 1.12.1+cu113
Tokenizers 0.12.1
