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fine-tune-distilbert-base-uncased-fine-tune-job-0-c5t25 – AI Model by rezabahmanzad | AlphaNeural AI
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fine-tune-distilbert-base-uncased-fine-tune-job-0-c5t25
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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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fine-tune-distilbert-base-uncased-fine-tune-job-0-c5t25
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: 0.3995
Accuracy: 0.83
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 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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4166
1.0
125
0.3995
0.83
0.1623
2.0
250
0.4124
0.8375
0.0578
3.0
375
0.4715
0.8325
Framework versions
Transformers 4.46.3
Pytorch 2.4.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
