End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: DayOne
+  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. -->
+
+# DayOne
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5286
+- Accuracy: 0.8686
+- F1 Macro: 0.6109
+- F1 Class 0: 0.9182
+- F1 Class 1: 0.0
+- F1 Class 2: 0.8817
+- F1 Class 3: 0.9091
+- F1 Class 4: 0.7556
+- F1 Class 5: 0.6667
+- F1 Class 6: 0.6897
+- F1 Class 7: 0.9701
+- F1 Class 8: 0.8889
+- F1 Class 9: 0.7500
+- F1 Class 10: 0.8926
+- F1 Class 11: 0.0
+- F1 Class 12: 0.7888
+- F1 Class 13: 0.0
+- F1 Class 14: 0.8213
+- F1 Class 15: 0.0
+- F1 Class 16: 0.0
+- F1 Class 17: 0.9772
+- F1 Class 18: 0.8381
+- F1 Class 19: 0.4706
+
+## 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 | Accuracy | F1 Macro | F1 Class 0 | F1 Class 1 | F1 Class 2 | F1 Class 3 | F1 Class 4 | F1 Class 5 | F1 Class 6 | F1 Class 7 | F1 Class 8 | F1 Class 9 | F1 Class 10 | F1 Class 11 | F1 Class 12 | F1 Class 13 | F1 Class 14 | F1 Class 15 | F1 Class 16 | F1 Class 17 | F1 Class 18 | F1 Class 19 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|
+| 0.9508        | 1.77  | 1000 | 0.5343          | 0.8708   | 0.6138   | 0.9245     | 0.0        | 0.8938     | 0.9091     | 0.7835     | 0.6966     | 0.6947     | 0.9762     | 0.8889     | 0.7723     | 0.8896      | 0.0         | 0.7932      | 0.0         | 0.8194      | 0.0         | 0.0         | 0.9772      | 0.7857      | 0.4706      |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.4
+- Tokenizers 0.13.3