metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top50_WithOOC_082023_MultilingualBertBase
results: []
SloBertAA_Top50_WithOOC_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: 1.6735
- Accuracy: 0.7607
- F1: 0.7597
- Precision: 0.7600
- Recall: 0.7607
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 |
|---|---|---|---|---|---|---|---|
| 1.2345 | 1.0 | 33346 | 1.1611 | 0.6809 | 0.6782 | 0.6864 | 0.6809 |
| 0.9498 | 2.0 | 66692 | 1.0380 | 0.7149 | 0.7106 | 0.7257 | 0.7149 |
| 0.7929 | 3.0 | 100038 | 0.9825 | 0.7368 | 0.7340 | 0.7384 | 0.7368 |
| 0.6319 | 4.0 | 133384 | 0.9972 | 0.7453 | 0.7436 | 0.7480 | 0.7453 |
| 0.4944 | 5.0 | 166730 | 1.0890 | 0.7479 | 0.7461 | 0.7498 | 0.7479 |
| 0.3771 | 6.0 | 200076 | 1.1597 | 0.7523 | 0.7506 | 0.7518 | 0.7523 |
| 0.2644 | 7.0 | 233422 | 1.3175 | 0.7553 | 0.7538 | 0.7547 | 0.7553 |
| 0.1736 | 8.0 | 266768 | 1.4977 | 0.7559 | 0.7549 | 0.7575 | 0.7559 |
| 0.1184 | 9.0 | 300114 | 1.6160 | 0.7595 | 0.7579 | 0.7580 | 0.7595 |
| 0.0784 | 10.0 | 333460 | 1.6735 | 0.7607 | 0.7597 | 0.7600 | 0.7607 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2