End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: email_question_extraction
+  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. -->
+
+# email_question_extraction
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Precision: 0.3143
+- Recall: 0.7097
+- F1: 0.4356
+- Accuracy: 0.9700
+
+## 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: 4
+- eval_batch_size: 4
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1978        | 1.0   | 91   | nan             | 0.2462    | 0.5161 | 0.3333 | 0.9763   |
+| 0.1749        | 2.0   | 182  | nan             | 0.3182    | 0.6774 | 0.4330 | 0.9681   |
+| 0.0351        | 3.0   | 273  | nan             | 0.2647    | 0.5806 | 0.3636 | 0.9779   |
+| 0.0434        | 4.0   | 364  | nan             | 0.3143    | 0.7097 | 0.4356 | 0.9700   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.0.0
+- Datasets 2.16.0
+- Tokenizers 0.15.0