End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- recall
+- precision
+model-index:
+- name: bert_imdb
+  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_imdb
+
+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: 0.3119
+- Accuracy: 0.9403
+- Recall: 0.9430
+- Precision: 0.9379
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
+| 0.2099        | 1.0   | 1563 | 0.2456          | 0.9102   | 0.8481 | 0.9683    |
+| 0.1379        | 2.0   | 3126 | 0.2443          | 0.9274   | 0.8911 | 0.9608    |
+| 0.0752        | 3.0   | 4689 | 0.2845          | 0.9391   | 0.9509 | 0.9290    |
+| 0.0352        | 4.0   | 6252 | 0.3119          | 0.9403   | 0.9430 | 0.9379    |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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