legalcase_outcome_model_v2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9549
- Accuracy: 0.3519
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.737 | 1.0 | 224 | 1.9877 | 0.3531 |
| 1.7261 | 2.0 | 448 | 1.9332 | 0.2984 |
| 1.6879 | 3.0 | 672 | 1.9163 | 0.3391 |
| 1.6007 | 4.0 | 896 | 1.9080 | 0.3369 |
| 1.3704 | 5.0 | 1120 | 1.9549 | 0.3519 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for Othniel74/legalcase_outcome_model_v2
Base model
distilbert/distilbert-base-uncased