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distilbert-base-uncased_fine_tunning – AI Model by adolford | AlphaNeural AI
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adolford
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distilbert-base-uncased_fine_tunning
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased_fine_tunning
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: 0.1959
Accuracy: 0.9595
Recall: 0.9677
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: 8
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Recall
0.1353
1.0
436
0.2021
0.9477
0.9847
0.0856
2.0
872
0.1983
0.9569
0.9592
0.0388
3.0
1308
0.1959
0.9595
0.9677
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
