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fine-tune-distilbert-base-uncased-fine-tune-job-1-bvwgm – AI Model by rezabahmanzad | AlphaNeural AI
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fine-tune-distilbert-base-uncased-fine-tune-job-1-bvwgm
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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-1-bvwgm
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: 0.4071
Accuracy: 0.805
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
0.4218
1.0
63
0.4250
0.815
0.3185
2.0
126
0.4071
0.805
0.1882
3.0
189
0.4157
0.835
Framework versions
Transformers 4.46.3
Pytorch 2.4.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
