End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: my_awesome_wnut_all_JGTt
+  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. -->
+
+# my_awesome_wnut_all_JGTt
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0375
+- Precision: 0.4267
+- Recall: 0.3478
+- F1: 0.3832
+- Accuracy: 0.9916
+
+## 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 251  | 0.0280          | 0.4259    | 0.25   | 0.3151 | 0.9918   |
+| 0.0294        | 2.0   | 502  | 0.0291          | 0.4324    | 0.3478 | 0.3855 | 0.9916   |
+| 0.0294        | 3.0   | 753  | 0.0355          | 0.4267    | 0.3478 | 0.3832 | 0.9915   |
+| 0.0084        | 4.0   | 1004 | 0.0375          | 0.4267    | 0.3478 | 0.3832 | 0.9916   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cpu
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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