End of training

README.md

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+---
+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
+should probably proofread and complete it, then remove this comment. -->
+
+# 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

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