Training complete

README.md

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+---
+base_model: mor40/BulBERT-chitanka-model
+tags:
+- generated_from_trainer
+datasets:
+- bgglue
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BulBERT-ner-udep-5epochs
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: bgglue
+      type: bgglue
+      config: udep
+      split: validation
+      args: udep
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.975273754856941
+    - name: Recall
+      type: recall
+      value: 0.975273754856941
+    - name: F1
+      type: f1
+      value: 0.975273754856941
+    - name: Accuracy
+      type: accuracy
+      value: 0.9777743637015415
+---
+
+<!-- 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. -->
+
+# BulBERT-ner-udep-5epochs
+
+This model is a fine-tuned version of [mor40/BulBERT-chitanka-model](https://huggingface.co/mor40/BulBERT-chitanka-model) on the bgglue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1089
+- Precision: 0.9753
+- Recall: 0.9753
+- F1: 0.9753
+- Accuracy: 0.9778
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1134        | 1.0   | 1114 | 0.0996          | 0.9674    | 0.9673 | 0.9673 | 0.9721   |
+| 0.0578        | 2.0   | 2228 | 0.0933          | 0.9728    | 0.9722 | 0.9725 | 0.9760   |
+| 0.0321        | 3.0   | 3342 | 0.0993          | 0.9739    | 0.9746 | 0.9743 | 0.9769   |
+| 0.0178        | 4.0   | 4456 | 0.1054          | 0.9746    | 0.9750 | 0.9748 | 0.9776   |
+| 0.0096        | 5.0   | 5570 | 0.1089          | 0.9753    | 0.9753 | 0.9753 | 0.9778   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1