End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert_base_data_wnut_17
+  results: []
+---
+
+<!-- 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. -->
+
+# distilbert_base_data_wnut_17
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2833
+- Precision: 0.5246
+- Recall: 0.3855
+- F1: 0.4444
+- 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  | 0.2740          | 0.6152    | 0.2919 | 0.3960 | 0.9404   |
+| No log        | 2.0   | 426  | 0.2568          | 0.5997    | 0.3679 | 0.4561 | 0.9450   |
+| 0.1764        | 3.0   | 639  | 0.2844          | 0.6269    | 0.3457 | 0.4456 | 0.9464   |
+| 0.1764        | 4.0   | 852  | 0.2963          | 0.5564    | 0.3522 | 0.4313 | 0.9459   |
+| 0.0526        | 5.0   | 1065 | 0.2833          | 0.5246    | 0.3855 | 0.4444 | 0.9461   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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