End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: my_awesome_model_2
+  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. -->
+
+# my_awesome_model_2
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1188
+- Accuracy: 0.9479
+- F1: 0.9507
+- Precision: 0.9389
+- Recall: 0.9628
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.4769        | 1.0   | 1225 | 0.4127          | 0.7860   | 0.7898 | 0.8100    | 0.7706 |
+| 0.4112        | 2.0   | 2450 | 0.3482          | 0.8268   | 0.8197 | 0.8972    | 0.7546 |
+| 0.3384        | 3.0   | 3675 | 0.2593          | 0.8856   | 0.8925 | 0.8760    | 0.9096 |
+| 0.2788        | 4.0   | 4900 | 0.1963          | 0.9140   | 0.9172 | 0.9217    | 0.9127 |
+| 0.2312        | 5.0   | 6125 | 0.1461          | 0.9400   | 0.9441 | 0.9179    | 0.9718 |
+| 0.1791        | 6.0   | 7350 | 0.1188          | 0.9479   | 0.9507 | 0.9389    | 0.9628 |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

runs/Sep01_23-36-40_1dd1a9185c5e/events.out.tfevents.1725246546.1dd1a9185c5e.36.1

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