metadata
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NEW_trained_slovak
results: []
NEW_trained_slovak
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1299
- Precision: 0.6938
- Recall: 0.7634
- F1: 0.7269
- Accuracy: 0.9709
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0808 | 1.0 | 530 | 0.1178 | 0.6792 | 0.75 | 0.7128 | 0.9686 |
| 0.0249 | 2.0 | 1061 | 0.1144 | 0.6708 | 0.7654 | 0.7150 | 0.9687 |
| 0.0122 | 3.0 | 1591 | 0.1206 | 0.6905 | 0.7741 | 0.7299 | 0.9708 |
| 0.0058 | 4.0 | 2120 | 0.1299 | 0.6938 | 0.7634 | 0.7269 | 0.9709 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2