End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: cis-lmu/glot500-base
+tags:
+- generated_from_trainer
+datasets:
+- universal_dependencies
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: glot500_model_ru_taiga
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: universal_dependencies
+      type: universal_dependencies
+      config: ru_taiga
+      split: test
+      args: ru_taiga
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8392572944297082
+    - name: Recall
+      type: recall
+      value: 0.8245595746898781
+    - name: F1
+      type: f1
+      value: 0.8318435166684194
+    - name: Accuracy
+      type: accuracy
+      value: 0.8491576589736098
+---
+
+<!-- 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. -->
+
+# glot500_model_ru_taiga
+
+This model is a fine-tuned version of [cis-lmu/glot500-base](https://huggingface.co/cis-lmu/glot500-base) on the universal_dependencies dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6914
+- Precision: 0.8393
+- Recall: 0.8246
+- F1: 0.8318
+- Accuracy: 0.8492
+
+## 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 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 197  | 1.0680          | 0.7495    | 0.7185 | 0.7337 | 0.7598   |
+| No log        | 2.0   | 394  | 0.6914          | 0.8393    | 0.8246 | 0.8318 | 0.8492   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1
+- Datasets 3.1.0
+- Tokenizers 0.20.3