Training complete

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-cased-finetuned_ADEs_SonatafyAI
+  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. -->
+
+# bert-base-cased-finetuned_ADEs_SonatafyAI
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3543
+- Precision: 0.3857
+- Recall: 0.4776
+- F1: 0.4268
+- Accuracy: 0.8554
+
+## 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-07
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.5644        | 1.0   | 640  | 0.4536          | 0.2717    | 0.3148 | 0.2916 | 0.8285   |
+| 0.4695        | 2.0   | 1280 | 0.3977          | 0.3292    | 0.4109 | 0.3656 | 0.8462   |
+| 0.4253        | 3.0   | 1920 | 0.3717          | 0.3653    | 0.4536 | 0.4047 | 0.8509   |
+| 0.3872        | 4.0   | 2560 | 0.3578          | 0.3747    | 0.4623 | 0.4139 | 0.8544   |
+| 0.3758        | 5.0   | 3200 | 0.3543          | 0.3857    | 0.4776 | 0.4268 | 0.8554   |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1