
	
		
	
	
		maestroqa-distilbert-negative-sentiment
	


This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on an unknown dataset.
It achieves the following results on the evaluation set:


Loss: 0.8880
Accuracy: 0.77



	
		
	
	
		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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5



	
		
	
	
		Training results
	



	
		
	
	
		Framework versions
	



Transformers 4.25.1
Pytorch 2.0.0
Datasets 2.10.1
Tokenizers 0.13.2




The maestroqa-distilbert-negative-sentiment model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english. It achieves a loss of 0.8880 and an accuracy of 0.77 on an evaluation set. However, further information is needed regarding the model's description, intended uses and limitations, training and evaluation data, and training procedure. The model was trained using specific hyperparameters, including a learning rate of 2e-05, a train batch size of 16, an eval batch size of 16, a seed of 42, and the Adam optimizer. The training was conducted over 5 epochs. The model was developed using the Transformers 4.25.1, PyTorch 2.0.0, Datasets 2.10.1, and Tokenizers 0.13.2 frameworks.

Platform did not provide a description for this model.

Arbazk

Models by this creator

maestroqa-distilbert-negative-sentiment

distilbert-base-uncased-finetuned-cola

distilbert-base-uncased-finetuned-sst2

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