metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top100_WithoutOOC_082023_MultilingualBertBase
results: []
SloBertAA_Top100_WithoutOOC_082023_MultilingualBertBase
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8490
- Accuracy: 0.6964
- F1: 0.6972
- Precision: 0.7001
- Recall: 0.6964
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.6988 | 1.0 | 44675 | 1.6287 | 0.5883 | 0.5902 | 0.6087 | 0.5883 |
| 1.3829 | 2.0 | 89350 | 1.4305 | 0.6351 | 0.6379 | 0.6563 | 0.6351 |
| 1.1122 | 3.0 | 134025 | 1.3339 | 0.6635 | 0.6651 | 0.6774 | 0.6635 |
| 0.881 | 4.0 | 178700 | 1.3128 | 0.6799 | 0.6805 | 0.6876 | 0.6799 |
| 0.7032 | 5.0 | 223375 | 1.3628 | 0.6831 | 0.6840 | 0.6932 | 0.6831 |
| 0.5454 | 6.0 | 268050 | 1.4343 | 0.6877 | 0.6890 | 0.6956 | 0.6877 |
| 0.408 | 7.0 | 312725 | 1.5546 | 0.6877 | 0.6888 | 0.6958 | 0.6877 |
| 0.2752 | 8.0 | 357400 | 1.6623 | 0.6932 | 0.6948 | 0.6992 | 0.6932 |
| 0.1844 | 9.0 | 402075 | 1.7825 | 0.6947 | 0.6959 | 0.6995 | 0.6947 |
| 0.1506 | 10.0 | 446750 | 1.8490 | 0.6964 | 0.6972 | 0.7001 | 0.6964 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2