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library_name: transformers
license: apache-2.0
base_model: PKOBP/polish-roberta-8k
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: mwik-classifier-xd
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. -->
# mwik-classifier-xd
This model is a fine-tuned version of [PKOBP/polish-roberta-8k](https://huggingface.co/PKOBP/polish-roberta-8k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1723
- Accuracy: 0.7561
- Precision: 0.7279
- Recall: 0.7561
- F1: 0.7335
## 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: 24
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- 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: polynomial
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 8
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 40 | 2.6964 | 0.4366 | 0.3391 | 0.4366 | 0.3326 |
| 3.1054 | 2.0 | 80 | 1.8682 | 0.6393 | 0.5160 | 0.6393 | 0.5555 |
| 2.1011 | 3.0 | 120 | 1.4782 | 0.7114 | 0.6120 | 0.7114 | 0.6473 |
| 1.5616 | 4.0 | 160 | 1.2761 | 0.7537 | 0.7102 | 0.7537 | 0.7116 |
| 1.2881 | 5.0 | 200 | 1.1802 | 0.7674 | 0.7394 | 0.7674 | 0.7318 |
| 1.2881 | 6.0 | 240 | 1.1084 | 0.7786 | 0.7529 | 0.7786 | 0.7527 |
| 1.112 | 7.0 | 280 | 1.0741 | 0.7836 | 0.7578 | 0.7836 | 0.7613 |
| 1.0374 | 8.0 | 320 | 1.0621 | 0.7848 | 0.7596 | 0.7848 | 0.7643 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
|