End of training

README.md

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+---
+license: apache-2.0
+base_model: google/electra-base-discriminator
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: electra-base-discriminator-finetuned-detests
+  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. -->
+
+# electra-base-discriminator-finetuned-detests
+
+This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1215
+- Accuracy: 0.7807
+- F1-score: 0.7308
+- Precision: 0.7162
+- Recall: 0.7768
+- Auc: 0.7768
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
+| 0.3236        | 1.0   | 174  | 0.4661          | 0.7610   | 0.6684   | 0.6647    | 0.6728 | 0.6728 |
+| 0.3239        | 2.0   | 348  | 0.4287          | 0.7987   | 0.7144   | 0.7138    | 0.7149 | 0.7149 |
+| 0.3421        | 3.0   | 522  | 0.5586          | 0.7741   | 0.7292   | 0.7163    | 0.7853 | 0.7853 |
+| 0.2288        | 4.0   | 696  | 0.6229          | 0.7807   | 0.7308   | 0.7162    | 0.7768 | 0.7768 |
+| 0.1888        | 5.0   | 870  | 0.6629          | 0.7954   | 0.7293   | 0.7173    | 0.7483 | 0.7483 |
+| 0.2205        | 6.0   | 1044 | 0.8462          | 0.8036   | 0.7349   | 0.7251    | 0.7485 | 0.7485 |
+| 0.1512        | 7.0   | 1218 | 0.8362          | 0.8151   | 0.7335   | 0.7367    | 0.7306 | 0.7306 |
+| 0.2345        | 8.0   | 1392 | 1.0372          | 0.7758   | 0.7204   | 0.7063    | 0.7584 | 0.7584 |
+| 0.0592        | 9.0   | 1566 | 1.0396          | 0.7840   | 0.7291   | 0.7142    | 0.7663 | 0.7663 |
+| 0.0381        | 10.0  | 1740 | 1.1215          | 0.7807   | 0.7308   | 0.7162    | 0.7768 | 0.7768 |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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