End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- wnut_17
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert_wnut_model
+  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: 0.5291073738680466
+    - name: Recall
+      type: recall
+      value: 0.3790546802594995
+    - name: F1
+      type: f1
+      value: 0.44168466522678185
+    - name: Accuracy
+      type: accuracy
+      value: 0.9476788920235958
+---
+
+<!-- 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. -->
+
+# bert_wnut_model
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3346
+- Precision: 0.5291
+- Recall: 0.3791
+- F1: 0.4417
+- Accuracy: 0.9477
+
+## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 213  | 0.2607          | 0.5443    | 0.2901 | 0.3785 | 0.9411   |
+| No log        | 2.0   | 426  | 0.2689          | 0.5474    | 0.3318 | 0.4132 | 0.9453   |
+| 0.1554        | 3.0   | 639  | 0.2896          | 0.5253    | 0.3753 | 0.4378 | 0.9475   |
+| 0.1554        | 4.0   | 852  | 0.3009          | 0.5079    | 0.3865 | 0.4389 | 0.9474   |
+| 0.0349        | 5.0   | 1065 | 0.3195          | 0.5109    | 0.3920 | 0.4436 | 0.9486   |
+| 0.0349        | 6.0   | 1278 | 0.3346          | 0.5291    | 0.3791 | 0.4417 | 0.9477   |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

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