End of training

README.md

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+---
+license: mit
+base_model: dslim/bert-base-NER
+tags:
+- generated_from_trainer
+datasets:
+- wnut_17
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: my_finetuned_wnut_model_1012
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wnut_17
+      type: wnut_17
+      config: wnut_17
+      split: test
+      args: wnut_17
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5479274611398963
+    - name: Recall
+      type: recall
+      value: 0.39202965708989806
+    - name: F1
+      type: f1
+      value: 0.45705024311183146
+    - name: Accuracy
+      type: accuracy
+      value: 0.9487047961015646
+---
+
+<!-- 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. -->
+
+# my_finetuned_wnut_model_1012
+
+This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2940
+- Precision: 0.5479
+- Recall: 0.3920
+- F1: 0.4571
+- Accuracy: 0.9487
+
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 213  | 0.2657          | 0.5157    | 0.3967 | 0.4484 | 0.9468   |
+| No log        | 2.0   | 426  | 0.2940          | 0.5479    | 0.3920 | 0.4571 | 0.9487   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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