metadata
license: apache-2.0
base_model: studio-ousia/mluke-large-lite
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: out
results: []
out
This model is a fine-tuned version of studio-ousia/mluke-large-lite on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1615
- Accuracy: 0.9399
- Precision: 0.9346
- Recall: 0.9460
- F1: 0.9403
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4109 | 1.0 | 1479 | 0.2462 | 0.9003 | 0.8710 | 0.9399 | 0.9041 |
| 0.1579 | 2.0 | 2958 | 0.1573 | 0.9399 | 0.9495 | 0.9293 | 0.9393 |
| 0.114 | 3.0 | 4437 | 0.1615 | 0.9399 | 0.9346 | 0.9460 | 0.9403 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1