Training complete

README.md

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+---
+license: apache-2.0
+base_model: Dr-BERT/DrBERT-7GB
+tags:
+- generated_from_trainer
+datasets:
+- quaero
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: drbert-7gb-finedtuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: quaero
+      type: quaero
+      config: emea
+      split: validation
+      args: emea
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7103274559193955
+    - name: Recall
+      type: recall
+      value: 0.7359081419624217
+    - name: F1
+      type: f1
+      value: 0.7228915662650602
+    - name: Accuracy
+      type: accuracy
+      value: 0.9223586595037094
+---
+
+<!-- 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. -->
+
+# drbert-7gb-finedtuned-ner
+
+This model is a fine-tuned version of [Dr-BERT/DrBERT-7GB](https://huggingface.co/Dr-BERT/DrBERT-7GB) on the quaero dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3775
+- Precision: 0.7103
+- Recall: 0.7359
+- F1: 0.7229
+- Accuracy: 0.9224
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 61   | 0.3947          | 0.7117    | 0.6905 | 0.7009 | 0.9198   |
+| No log        | 2.0   | 122  | 0.3738          | 0.7210    | 0.7244 | 0.7227 | 0.9224   |
+| No log        | 3.0   | 183  | 0.3775          | 0.7103    | 0.7359 | 0.7229 | 0.9224   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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