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---
license: cc-by-nc-sa-4.0
base_model: ufal/robeczech-base
tags:
- generated_from_trainer
datasets:
- cnec
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: CNEC_2_0_ext_robeczech-base
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cnec
type: cnec
config: default
split: validation
args: default
metrics:
- name: Precision
type: precision
value: 0.8633093525179856
- name: Recall
type: recall
value: 0.8933002481389578
- name: F1
type: f1
value: 0.8780487804878048
- name: Accuracy
type: accuracy
value: 0.9703429462197973
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CNEC_2_0_ext_robeczech-base
This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on the cnec dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1663
- Precision: 0.8633
- Recall: 0.8933
- F1: 0.8780
- Accuracy: 0.9703
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2593 | 4.46 | 1000 | 0.1653 | 0.8195 | 0.8223 | 0.8209 | 0.9593 |
| 0.1209 | 8.93 | 2000 | 0.1355 | 0.8441 | 0.8789 | 0.8612 | 0.9679 |
| 0.0763 | 13.39 | 3000 | 0.1310 | 0.8591 | 0.8893 | 0.8739 | 0.9709 |
| 0.0539 | 17.86 | 4000 | 0.1383 | 0.8656 | 0.8953 | 0.8802 | 0.9719 |
| 0.0403 | 22.32 | 5000 | 0.1392 | 0.8626 | 0.8943 | 0.8782 | 0.9710 |
| 0.0316 | 26.79 | 6000 | 0.1539 | 0.8606 | 0.8948 | 0.8774 | 0.9712 |
| 0.0254 | 31.25 | 7000 | 0.1552 | 0.8660 | 0.8913 | 0.8785 | 0.9706 |
| 0.0211 | 35.71 | 8000 | 0.1621 | 0.8658 | 0.8968 | 0.8810 | 0.9701 |
| 0.0183 | 40.18 | 9000 | 0.1593 | 0.8688 | 0.8973 | 0.8828 | 0.9718 |
| 0.0161 | 44.64 | 10000 | 0.1638 | 0.8653 | 0.8993 | 0.8820 | 0.9714 |
| 0.015 | 49.11 | 11000 | 0.1663 | 0.8633 | 0.8933 | 0.8780 | 0.9703 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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