metadata
license: apache-2.0
base_model: studio-ousia/luke-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: luke-base-paper-setup
results: []
luke-base-paper-setup
This model is a fine-tuned version of studio-ousia/luke-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3800
- Accuracy: 0.8426
- Precision: 0.8465
- Recall: 0.8370
- F1: 0.8417
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5192 | 1.0 | 1074 | 0.4464 | 0.8063 | 0.8263 | 0.7756 | 0.8001 |
| 0.3708 | 2.0 | 2148 | 0.3782 | 0.8315 | 0.8365 | 0.8241 | 0.8303 |
| 0.3191 | 3.0 | 3222 | 0.3800 | 0.8426 | 0.8465 | 0.8370 | 0.8417 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0