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-multiple-choice
results: []
luke-base-multiple-choice
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: 0.3865
- Accuracy: 0.8188
- Precision: 0.8255
- Recall: 0.8086
- F1: 0.8169
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 269 | 0.6912 | 0.6434 | 0.6713 | 0.5620 | 0.6118 |
| 0.6088 | 2.0 | 538 | 0.4058 | 0.8107 | 0.8139 | 0.8056 | 0.8098 |
| 0.6088 | 3.0 | 807 | 0.3865 | 0.8188 | 0.8255 | 0.8086 | 0.8169 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0