End of training

README.md

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+---
+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: Goader_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: 0.7423200924863519
+    - name: Recall
+      type: recall
+      value: 0.6864113851587973
+    - name: F1
+      type: f1
+      value: 0.6947659539044735
+    - name: Accuracy
+      type: accuracy
+      value: 0.8409785932721713
+---
+
+<!-- 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. -->
+
+# Goader_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: 0.3890
+- Precision: 0.7423
+- Recall: 0.6864
+- F1: 0.6948
+- Accuracy: 0.8410
+
+## 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: 32
+- 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
+
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 1.11.0a0+17540c5
+- Datasets 2.21.0
+- Tokenizers 0.15.2

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