metadata
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_B09
results: []
BERT_B09
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2572
- Precision: 0.6376
- Recall: 0.6753
- F1: 0.6559
- Accuracy: 0.9287
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- label_smoothing_factor: 0.001
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4255 | 1.0 | 46 | 0.3653 | 0.4807 | 0.5043 | 0.4922 | 0.9019 |
| 0.2621 | 2.0 | 92 | 0.2719 | 0.6056 | 0.6101 | 0.6078 | 0.9227 |
| 0.1642 | 3.0 | 138 | 0.2659 | 0.6047 | 0.6605 | 0.6314 | 0.9246 |
| 0.1249 | 4.0 | 184 | 0.2580 | 0.6382 | 0.6617 | 0.6498 | 0.9299 |
| 0.1232 | 5.0 | 230 | 0.2572 | 0.6376 | 0.6753 | 0.6559 | 0.9287 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3