Model save

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- recall
+- precision
+- f1
+model-index:
+- name: checkpoint-126-5ep3bsfrmulti1
+  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-126-5ep3bsfrmulti1
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2333
+- Recall: 0.9032
+- Precision: 0.875
+- F1: 0.8889
+- Roc Auc: 0.0933
+
+## 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: 97
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1     | Roc Auc |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:-------:|
+| 0.0011        | 1.0   | 97   | 0.2333          | 0.9032 | 0.875     | 0.8889 | 0.0933  |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu118
+- Datasets 2.17.0
+- Tokenizers 0.15.2