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_2layers
results: []
czert_lr2e-05_bs4_train287_max_len256_2layers
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: 0.1713
- Precision: 0.9107
- Recall: 0.9212
- F1: 0.9159
- Accuracy: 0.9513
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 | 0.5136 | 0.6578 | 0.6470 | 0.6524 | 0.8319 |
| No log | 2.0 | 144 | 0.2634 | 0.8669 | 0.8682 | 0.8676 | 0.9286 |
| No log | 3.0 | 216 | 0.2205 | 0.9024 | 0.8749 | 0.8885 | 0.9389 |
| No log | 4.0 | 288 | 0.1857 | 0.9059 | 0.8976 | 0.9018 | 0.9464 |
| No log | 5.0 | 360 | 0.1767 | 0.9111 | 0.9058 | 0.9085 | 0.9508 |
| No log | 6.0 | 432 | 0.1698 | 0.9216 | 0.9198 | 0.9207 | 0.9552 |
| 0.2996 | 7.0 | 504 | 0.1674 | 0.9266 | 0.9198 | 0.9232 | 0.9571 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.20.0