legal-bert-sentiment-small-10000

This model is a fine-tuned version of nlpaueb/legal-bert-small-uncased on the imdb dataset with 10000 train samples and 1200 test samples.. It achieves the following results on the evaluation set:

• Loss: 0.2959
• Accuracy: 0.885
• F1: 0.8846
• Precision: 0.8831
• Recall: 0.8861

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: 5e-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: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	313	0.3317	0.8667	0.8728	0.8306	0.9196
0.3554	2.0	626	0.2959	0.885	0.8846	0.8831	0.8861

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0