End of training

README.md

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+---
+library_name: transformers
+license: cc-by-4.0
+base_model: Goader/liberta-large
+tags:
+- generated_from_trainer
+datasets:
+- universal_dependencies
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: liberta-large-upos
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: universal_dependencies
+      type: universal_dependencies
+      config: uk_iu
+      split: validation
+      args: uk_iu
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8100632457506624
+    - name: Recall
+      type: recall
+      value: 0.7466487546768732
+    - name: F1
+      type: f1
+      value: 0.7541998712736135
+    - name: Accuracy
+      type: accuracy
+      value: 0.8675486133248327
+---
+
+<!-- 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. -->
+
+# liberta-large-upos
+
+This model is a fine-tuned version of [Goader/liberta-large](https://huggingface.co/Goader/liberta-large) on the universal_dependencies dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3346
+- Precision: 0.8101
+- Recall: 0.7466
+- F1: 0.7542
+- Accuracy: 0.8675
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 338  | 1.0412          | 0.5939    | 0.4306 | 0.4617 | 0.5790   |
+| No log        | 2.0   | 676  | 0.6850          | 0.6114    | 0.5788 | 0.5745 | 0.7115   |
+| No log        | 3.0   | 1014 | 0.6075          | 0.6787    | 0.6205 | 0.6241 | 0.7389   |
+| No log        | 4.0   | 1352 | 0.5585          | 0.7178    | 0.6393 | 0.6425 | 0.7608   |
+| No log        | 5.0   | 1690 | 0.4762          | 0.7424    | 0.6737 | 0.6874 | 0.7984   |
+| No log        | 6.0   | 2028 | 0.4203          | 0.7159    | 0.6962 | 0.6946 | 0.8228   |
+| No log        | 7.0   | 2366 | 0.4275          | 0.7403    | 0.7081 | 0.7028 | 0.8205   |
+| No log        | 8.0   | 2704 | 0.3789          | 0.7909    | 0.7189 | 0.7282 | 0.8470   |
+| No log        | 9.0   | 3042 | 0.3431          | 0.8051    | 0.7415 | 0.7484 | 0.8626   |
+| No log        | 10.0  | 3380 | 0.3346          | 0.8101    | 0.7466 | 0.7542 | 0.8675   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1