End of training

README.md

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+---
+license: mit
+base_model: cointegrated/rubert-tiny2
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: my_awesome_wnut_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. -->
+
+# my_awesome_wnut_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: 0.1997
+- Precision: 0.3076
+- Recall: 0.4690
+- F1: 0.3716
+- Accuracy: 0.9322
+
+## 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: 7
+- eval_batch_size: 7
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 24
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.621         | 2.41  | 140  | 0.4025          | 0.0       | 0.0    | 0.0    | 0.9050   |
+| 0.3224        | 4.83  | 280  | 0.2750          | 0.2036    | 0.2074 | 0.2055 | 0.9118   |
+| 0.2421        | 7.24  | 420  | 0.2326          | 0.2706    | 0.3406 | 0.3016 | 0.9220   |
+| 0.2061        | 9.66  | 560  | 0.2146          | 0.2968    | 0.4102 | 0.3444 | 0.9269   |
+| 0.1779        | 12.07 | 700  | 0.2037          | 0.3125    | 0.4257 | 0.3604 | 0.9306   |
+| 0.1606        | 14.48 | 840  | 0.2042          | 0.3044    | 0.4613 | 0.3668 | 0.9298   |
+| 0.1544        | 16.9  | 980  | 0.2001          | 0.3101    | 0.4690 | 0.3734 | 0.9310   |
+| 0.1402        | 19.31 | 1120 | 0.1991          | 0.3130    | 0.4690 | 0.3755 | 0.9316   |
+| 0.139         | 21.72 | 1260 | 0.1997          | 0.3076    | 0.4690 | 0.3716 | 0.9322   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

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