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distilbert-base-uncased-lora-text-classification – AI Model by smend0 | AlphaNeural AI
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smend0
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distilbert-base-uncased-lora-text-classification
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tensorboard
safetensors
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
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distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of
distilbert-base-uncased
on a truncated IMDB dataset. It achieves the following results on the evaluation set:
Loss: 1.7208
Accuracy: {'accuracy': 0.876}
Model description
The purpose of this model is to turn distilbert into a sentiment classification model.
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.001
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
250
2.0890
{'accuracy': 0.862}
0.2005
2.0
500
1.8919
{'accuracy': 0.874}
0.2005
3.0
750
1.7205
{'accuracy': 0.871}
0.0963
4.0
1000
1.7208
{'accuracy': 0.876}
Framework versions
Transformers 4.37.1
Pytorch 2.1.2+cu118
Datasets 2.16.1
Tokenizers 0.15.1
