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---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robeczech_lr3e-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_lr3e-05_bs16_train287
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1179
- Precision: 0.9454
- Recall: 0.9595
- F1: 0.9524
- Accuracy: 0.9714
## 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: 3e-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 | 1.1550 | 1.0 | 0.0005 | 0.0010 | 0.5668 |
| No log | 2.0 | 36 | 0.4725 | 0.7099 | 0.7006 | 0.7052 | 0.8587 |
| No log | 3.0 | 54 | 0.2293 | 0.8740 | 0.8643 | 0.8691 | 0.9351 |
| No log | 4.0 | 72 | 0.1474 | 0.9224 | 0.9126 | 0.9175 | 0.9565 |
| No log | 5.0 | 90 | 0.1210 | 0.9457 | 0.9411 | 0.9434 | 0.9697 |
| No log | 6.0 | 108 | 0.1212 | 0.9409 | 0.9382 | 0.9396 | 0.9674 |
| No log | 7.0 | 126 | 0.1067 | 0.9540 | 0.9517 | 0.9529 | 0.9740 |
| No log | 8.0 | 144 | 0.0918 | 0.9574 | 0.9551 | 0.9562 | 0.9753 |
| No log | 9.0 | 162 | 0.1076 | 0.9549 | 0.9517 | 0.9533 | 0.9749 |
| No log | 10.0 | 180 | 0.0990 | 0.9599 | 0.9585 | 0.9592 | 0.9774 |
| No log | 11.0 | 198 | 0.1027 | 0.9673 | 0.9570 | 0.9621 | 0.9778 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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