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_cl_size2
results: []
czert_lr2e-05_bs4_train287_cl_size2
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: 0.1715
- Precision: 0.9099
- Recall: 0.9222
- F1: 0.9160
- Accuracy: 0.9529
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 72 | 0.4681 | 0.7251 | 0.7489 | 0.7368 | 0.8673 |
| No log | 2.0 | 144 | 0.2397 | 0.8668 | 0.8860 | 0.8763 | 0.9332 |
| No log | 3.0 | 216 | 0.2036 | 0.9032 | 0.8875 | 0.8953 | 0.9429 |
| No log | 4.0 | 288 | 0.1787 | 0.9071 | 0.9150 | 0.9111 | 0.9508 |
| No log | 5.0 | 360 | 0.1585 | 0.9253 | 0.9213 | 0.9233 | 0.9586 |
| No log | 6.0 | 432 | 0.1683 | 0.9176 | 0.9194 | 0.9185 | 0.9567 |
| 0.2732 | 7.0 | 504 | 0.1641 | 0.9310 | 0.9189 | 0.9249 | 0.9588 |
| 0.2732 | 8.0 | 576 | 0.1746 | 0.9256 | 0.9256 | 0.9256 | 0.9596 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1