metadata
library_name: transformers
base_model: UWB-AIR/Czert-B-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: czert_lr2e-05_bs4_train287_max_len256
results: []
czert_lr2e-05_bs4_train287_max_len256
This model is a fine-tuned version of UWB-AIR/Czert-B-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1677
- Precision: 0.9165
- Recall: 0.9328
- F1: 0.9246
- Accuracy: 0.9561
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: 4
- eval_batch_size: 4
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 72 | 0.2932 | 0.8413 | 0.8522 | 0.8467 | 0.9163 |
| No log | 2.0 | 144 | 0.1967 | 0.8936 | 0.8885 | 0.8910 | 0.9391 |
| No log | 3.0 | 216 | 0.1875 | 0.9168 | 0.8885 | 0.9024 | 0.9458 |
| No log | 4.0 | 288 | 0.1647 | 0.9079 | 0.9087 | 0.9083 | 0.9504 |
| No log | 5.0 | 360 | 0.1658 | 0.9298 | 0.9078 | 0.9186 | 0.9544 |
| No log | 6.0 | 432 | 0.1602 | 0.9258 | 0.9276 | 0.9267 | 0.9590 |
| 0.1926 | 7.0 | 504 | 0.1642 | 0.9209 | 0.9223 | 0.9216 | 0.9565 |
| 0.1926 | 8.0 | 576 | 0.1697 | 0.9298 | 0.9271 | 0.9284 | 0.9602 |
| 0.1926 | 9.0 | 648 | 0.1679 | 0.9287 | 0.9247 | 0.9267 | 0.9590 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.20.0