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---
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
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