metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-combined-large
results: []
distilbert-combined-large
This model is a fine-tuned version of dbmdz/distilbert-base-turkish-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3131
- Accuracy: 0.8811
- F1: 0.8814
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: 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 | F1 |
|---|---|---|---|---|---|
| 0.3116 | 1.0 | 3077 | 0.3040 | 0.8752 | 0.8731 |
| 0.2552 | 2.0 | 6154 | 0.3053 | 0.8776 | 0.8755 |
| 0.2101 | 3.0 | 9231 | 0.3131 | 0.8811 | 0.8814 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1