Model save

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- recall
+- precision
+- f1
+model-index:
+- name: checkpoint-194-5ep3bsfrmulti3
+  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. -->
+
+# checkpoint-194-5ep3bsfrmulti3
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1347
+- Recall: 0.9355
+- Precision: 0.9355
+- F1: 0.9355
+- Roc Auc: 0.9702
+
+## 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: 5e-05
+- train_batch_size: 3
+- eval_batch_size: 3
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 291
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1     | Roc Auc |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:-------:|
+| 0.2212        | 0.33  | 97   | 1.1492          | 0.4839 | 1.0       | 0.6522 | 0.9092  |
+| 0.233         | 1.33  | 194  | 0.3849          | 0.9677 | 0.6977    | 0.8108 | 0.6710  |
+| 0.0004        | 2.33  | 291  | 0.1347          | 0.9355 | 0.9355    | 0.9355 | 0.9702  |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu118
+- Datasets 2.17.0
+- Tokenizers 0.15.2