End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- wnut_17
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: my_awesome_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: 0.5485122897800776
+    - name: Recall
+      type: recall
+      value: 0.39295644114921224
+    - name: F1
+      type: f1
+      value: 0.45788336933045354
+    - name: Accuracy
+      type: accuracy
+      value: 0.9461331281262024
+---
+
+<!-- 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_awesome_wnut_model
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2926
+- Precision: 0.5485
+- Recall: 0.3930
+- F1: 0.4579
+- Accuracy: 0.9461
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 213  | 0.2744          | 0.6308    | 0.2660 | 0.3742 | 0.9396   |
+| No log        | 2.0   | 426  | 0.2644          | 0.6006    | 0.3457 | 0.4388 | 0.9438   |
+| 0.1817        | 3.0   | 639  | 0.2953          | 0.6426    | 0.3466 | 0.4503 | 0.9456   |
+| 0.1817        | 4.0   | 852  | 0.3107          | 0.5796    | 0.3577 | 0.4424 | 0.9455   |
+| 0.0532        | 5.0   | 1065 | 0.2926          | 0.5485    | 0.3930 | 0.4579 | 0.9461   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

model.safetensors

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