InLegalBERT-fine-tuned – AI Model by Chandrababu-Namani | AlphaNeural AI

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Chandrababu-Namani/
InLegalBERT-fine-tuned

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text-classification

generated_from_trainer

law-ai/InLegalBERT

autotrain_compatible

endpoints_compatible

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InLegalBERT-lora-text-classification

This model is a fine-tuned version of law-ai/InLegalBERT on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0550
Accuracy: {'accuracy': 0.6449893390191898}

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	235	1.1448	{'accuracy': 0.6151385927505331}
No log	2.0	470	1.0553	{'accuracy': 0.6380597014925373}
1.2222	3.0	705	1.0427	{'accuracy': 0.6316631130063965}
1.2222	4.0	940	1.0490	{'accuracy': 0.6428571428571429}
0.8111	5.0	1175	1.0550	{'accuracy': 0.6449893390191898}

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1