---
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_train287
  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_train287

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: 0.2219
- Precision: 0.9364
- Recall: 0.9516
- F1: 0.9439
- Accuracy: 0.9681

## 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   | 18   | 1.6464          | 0.0       | 0.0    | 0.0    | 0.5666   |
| No log        | 2.0   | 36   | 1.3151          | 1.0       | 0.0005 | 0.0010 | 0.5668   |
| No log        | 3.0   | 54   | 1.1082          | 0.3172    | 0.2849 | 0.3002 | 0.6802   |
| No log        | 4.0   | 72   | 0.9408          | 0.5488    | 0.5292 | 0.5388 | 0.7882   |
| No log        | 5.0   | 90   | 0.7478          | 0.6970    | 0.6953 | 0.6962 | 0.8571   |
| No log        | 6.0   | 108  | 0.5949          | 0.7631    | 0.7716 | 0.7673 | 0.8895   |
| No log        | 7.0   | 126  | 0.4931          | 0.8374    | 0.8479 | 0.8426 | 0.9221   |
| No log        | 8.0   | 144  | 0.4231          | 0.8736    | 0.8846 | 0.8791 | 0.9393   |
| No log        | 9.0   | 162  | 0.3772          | 0.8838    | 0.8923 | 0.8880 | 0.9437   |
| No log        | 10.0  | 180  | 0.3473          | 0.8852    | 0.8938 | 0.8895 | 0.9447   |
| No log        | 11.0  | 198  | 0.3302          | 0.8907    | 0.8972 | 0.8939 | 0.9473   |
| No log        | 12.0  | 216  | 0.3165          | 0.8893    | 0.9000 | 0.8946 | 0.9466   |
| No log        | 13.0  | 234  | 0.3041          | 0.8912    | 0.8976 | 0.8944 | 0.9473   |
| No log        | 14.0  | 252  | 0.2940          | 0.8946    | 0.8972 | 0.8959 | 0.9483   |
| No log        | 15.0  | 270  | 0.2898          | 0.8936    | 0.9005 | 0.8971 | 0.9481   |
| No log        | 16.0  | 288  | 0.2823          | 0.8924    | 0.9010 | 0.8967 | 0.9481   |
| No log        | 17.0  | 306  | 0.2777          | 0.8941    | 0.9010 | 0.8975 | 0.9487   |
| No log        | 18.0  | 324  | 0.2717          | 0.8972    | 0.9020 | 0.8996 | 0.9500   |
| No log        | 19.0  | 342  | 0.2644          | 0.9034    | 0.9078 | 0.9056 | 0.9523   |
| No log        | 20.0  | 360  | 0.2585          | 0.9051    | 0.9116 | 0.9083 | 0.9535   |
| No log        | 21.0  | 378  | 0.2523          | 0.9131    | 0.9184 | 0.9157 | 0.9567   |
| No log        | 22.0  | 396  | 0.2523          | 0.9136    | 0.9189 | 0.9162 | 0.9569   |
| No log        | 23.0  | 414  | 0.2473          | 0.9177    | 0.9256 | 0.9216 | 0.9590   |
| No log        | 24.0  | 432  | 0.2476          | 0.9186    | 0.9261 | 0.9223 | 0.9592   |
| No log        | 25.0  | 450  | 0.2443          | 0.9198    | 0.9252 | 0.9225 | 0.9594   |
| No log        | 26.0  | 468  | 0.2439          | 0.9189    | 0.9247 | 0.9218 | 0.9592   |
| No log        | 27.0  | 486  | 0.2407          | 0.9203    | 0.9256 | 0.9230 | 0.9596   |
| 0.4988        | 28.0  | 504  | 0.2393          | 0.9207    | 0.9252 | 0.9229 | 0.9598   |
| 0.4988        | 29.0  | 522  | 0.2397          | 0.9204    | 0.9266 | 0.9235 | 0.9598   |
| 0.4988        | 30.0  | 540  | 0.2392          | 0.9214    | 0.9281 | 0.9247 | 0.9604   |


### Framework versions

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