---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: ufal/robeczech-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robeczech_lr1e-05_bs16_train150
  results: []
---

<!-- 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. -->

# robeczech_lr1e-05_bs16_train150

This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3536
- Precision: 0.8941
- Recall: 0.9034
- F1: 0.8987
- Accuracy: 0.9477

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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   | 10   | 1.8823          | 0.0       | 0.0    | 0.0    | 0.5666   |
| No log        | 2.0   | 20   | 1.6416          | 0.0       | 0.0    | 0.0    | 0.5666   |
| No log        | 3.0   | 30   | 1.4591          | 0.0       | 0.0    | 0.0    | 0.5666   |
| No log        | 4.0   | 40   | 1.2836          | 0.375     | 0.0217 | 0.0411 | 0.5760   |
| No log        | 5.0   | 50   | 1.1520          | 0.4166    | 0.2665 | 0.3251 | 0.6794   |
| No log        | 6.0   | 60   | 1.0409          | 0.4572    | 0.4070 | 0.4307 | 0.7363   |
| No log        | 7.0   | 70   | 0.9407          | 0.6091    | 0.5794 | 0.5939 | 0.8093   |
| No log        | 8.0   | 80   | 0.8449          | 0.6839    | 0.6779 | 0.6809 | 0.8485   |
| No log        | 9.0   | 90   | 0.7620          | 0.7035    | 0.7079 | 0.7057 | 0.8602   |
| No log        | 10.0  | 100  | 0.6857          | 0.7370    | 0.7349 | 0.7360 | 0.8738   |
| No log        | 11.0  | 110  | 0.6316          | 0.7570    | 0.7610 | 0.7590 | 0.8845   |
| No log        | 12.0  | 120  | 0.5793          | 0.7782    | 0.7793 | 0.7788 | 0.8937   |
| No log        | 13.0  | 130  | 0.5451          | 0.7977    | 0.7996 | 0.7986 | 0.9016   |
| No log        | 14.0  | 140  | 0.5131          | 0.8194    | 0.8238 | 0.8216 | 0.9127   |
| No log        | 15.0  | 150  | 0.4870          | 0.8508    | 0.8479 | 0.8493 | 0.9253   |
| No log        | 16.0  | 160  | 0.4638          | 0.8601    | 0.8580 | 0.8591 | 0.9297   |
| No log        | 17.0  | 170  | 0.4476          | 0.8615    | 0.8682 | 0.8648 | 0.9316   |
| No log        | 18.0  | 180  | 0.4290          | 0.8755    | 0.8730 | 0.8743 | 0.9364   |
| No log        | 19.0  | 190  | 0.4160          | 0.8792    | 0.8817 | 0.8804 | 0.9391   |
| No log        | 20.0  | 200  | 0.4037          | 0.8841    | 0.8841 | 0.8841 | 0.9410   |
| No log        | 21.0  | 210  | 0.3962          | 0.8850    | 0.8885 | 0.8867 | 0.9418   |
| No log        | 22.0  | 220  | 0.3911          | 0.8831    | 0.8865 | 0.8848 | 0.9404   |
| No log        | 23.0  | 230  | 0.3850          | 0.8850    | 0.8880 | 0.8865 | 0.9416   |
| No log        | 24.0  | 240  | 0.3817          | 0.8869    | 0.8827 | 0.8848 | 0.9408   |
| No log        | 25.0  | 250  | 0.3764          | 0.8879    | 0.8875 | 0.8877 | 0.9424   |
| No log        | 26.0  | 260  | 0.3730          | 0.8857    | 0.8870 | 0.8864 | 0.9416   |
| No log        | 27.0  | 270  | 0.3691          | 0.8888    | 0.8880 | 0.8884 | 0.9427   |
| No log        | 28.0  | 280  | 0.3663          | 0.8877    | 0.8889 | 0.8883 | 0.9427   |
| No log        | 29.0  | 290  | 0.3657          | 0.8881    | 0.8894 | 0.8888 | 0.9429   |
| No log        | 30.0  | 300  | 0.3658          | 0.8880    | 0.8885 | 0.8882 | 0.9427   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1