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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: bert-base-uncased-ft-imdb
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert-base-uncased-ft-imdb
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2556
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- Accuracy: 0.945
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- F1: 0.9441
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.2943 | 0.38 | 750 | 0.1877 | 0.9257 | 0.9226 |
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| 0.2133 | 0.75 | 1500 | 0.1806 | 0.9375 | 0.9347 |
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| 0.1811 | 1.12 | 2250 | 0.1783 | 0.9443 | 0.9434 |
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| 0.1274 | 1.5 | 3000 | 0.2072 | 0.942 | 0.9400 |
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| 0.1177 | 1.88 | 3750 | 0.2737 | 0.9325 | 0.9336 |
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| 0.0817 | 2.25 | 4500 | 0.2706 | 0.9435 | 0.9420 |
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| 0.0644 | 2.62 | 5250 | 0.2630 | 0.9447 | 0.9434 |
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| 0.0604 | 3.0 | 6000 | 0.2556 | 0.945 | 0.9441 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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