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florspag/
distilbert-base-uncased-lora-financial-sentiment-analysis

Name: distilbert-base-uncased-lora-financial-sentiment-analysis
Availability: InStock

peft

tensorboard

safetensors

generated_from_trainer

financial_phrasebank

distilbert/distilbert-base-uncased

adapter

apache-2.0

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distilbert-base-uncased-lora-financial-sentiment-analysis

This model is a fine-tuned version of distilbert-base-uncased on the financial_phrasebank dataset. It achieves the following results on the evaluation set:

Loss: 0.0777
Accuracy: {'accuracy': 0.9779735682819384}

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: 4
eval_batch_size: 4
seed: 42
optimizer: Use OptimizerNames.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
0.3107	1.0	510	0.0777	{'accuracy': 0.9779735682819384}
0.117	2.0	1020	0.0853	{'accuracy': 0.9691629955947136}
0.0652	3.0	1530	0.0841	{'accuracy': 0.9779735682819384}

Framework versions

PEFT 0.13.2
Transformers 4.46.2
Pytorch 2.5.1
Datasets 3.1.0
Tokenizers 0.20.3

florspag/distilbert-base-uncased-lora-financial-sentiment-analysis

distilbert-base-uncased-lora-financial-sentiment-analysis

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

florspag/
distilbert-base-uncased-lora-financial-sentiment-analysis