metadata
library_name: transformers
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-small-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: legal-bert-sentiment-small-10000
results: []
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