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_serbian
results: []
NEW_trained_serbian
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: 0.0749
- Precision: 0.8652
- Recall: 0.9028
- F1: 0.8836
- Accuracy: 0.9820
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 208 | 0.0799 | 0.8002 | 0.8599 | 0.8290 | 0.9742 |
| No log | 2.0 | 416 | 0.0733 | 0.8322 | 0.8979 | 0.8638 | 0.9802 |
| 0.0902 | 3.0 | 624 | 0.0709 | 0.8736 | 0.9003 | 0.8867 | 0.9829 |
| 0.0902 | 4.0 | 832 | 0.0749 | 0.8652 | 0.9028 | 0.8836 | 0.9820 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2