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distilbert-base-uncased-lora-text-classification – AI Model by whoshubham | AlphaNeural AI
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whoshubham
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distilbert-base-uncased-lora-text-classification
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peft
tensorboard
safetensors
generated_from_trainer
distilbert/distilbert-base-uncased
adapter
apache-2.0
us
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distilbert-base-uncased-lora-text-classification
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: 0.2504
Accuracy: {'accuracy': 0.903}
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: 0.001
train_batch_size: 50
eval_batch_size: 50
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
20
0.3354
{'accuracy': 0.884}
No log
2.0
40
0.2676
{'accuracy': 0.901}
No log
3.0
60
0.2518
{'accuracy': 0.895}
No log
4.0
80
0.2504
{'accuracy': 0.903}
Framework versions
PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1
