End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-baseline
+  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-baseline
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3081
+- Accuracy: 0.9221
+- Precision: 0.4610
+- Recall: 0.5
+- F1: 0.4797
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.3338        | 1.0   | 90   | 0.2731          | 0.9221   | 0.4610    | 0.5    | 0.4797 |
+| 0.3228        | 2.0   | 180  | 0.2609          | 0.9221   | 0.4610    | 0.5    | 0.4797 |
+| 0.2426        | 3.0   | 270  | 0.3081          | 0.9221   | 0.4610    | 0.5    | 0.4797 |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.1
+- Datasets 4.4.1
+- Tokenizers 0.22.1

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