---
library_name: transformers
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: slot_token_classification_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# slot_token_classification_model

This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4739
- Precision: 0.6455
- Recall: 0.7092
- F1: 0.6758
- Accuracy: 0.8977

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.408         | 1.0   | 720  | 0.4998          | 0.6226    | 0.6688 | 0.6449 | 0.8909   |
| 0.3758        | 2.0   | 1440 | 0.4815          | 0.6349    | 0.6868 | 0.6598 | 0.8953   |
| 0.3383        | 3.0   | 2160 | 0.4746          | 0.6405    | 0.7002 | 0.6690 | 0.8958   |
| 0.3278        | 4.0   | 2880 | 0.4733          | 0.6577    | 0.7032 | 0.6797 | 0.8977   |
| 0.3053        | 5.0   | 3600 | 0.4739          | 0.6455    | 0.7092 | 0.6758 | 0.8977   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0