metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: results
results: []
results
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0956
- Accuracy: 0.9714
- Precision: 0.9704
- Recall: 0.9714
- F1 Score: 0.9708
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|---|---|---|---|---|---|---|---|
| 0.2725 | 1.0 | 507 | 0.2315 | 0.9388 | 0.8813 | 0.9388 | 0.9091 |
| 0.2883 | 2.0 | 1014 | 0.2167 | 0.9388 | 0.8813 | 0.9388 | 0.9091 |
| 0.0762 | 3.0 | 1521 | 0.0956 | 0.9714 | 0.9704 | 0.9714 | 0.9708 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3