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library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: imdb_bert
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. -->
# imdb_bert
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5157
- Accuracy: 0.9400
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2773 | 1.0 | 782 | 0.1822 | 0.9289 |
| 0.1226 | 2.0 | 1564 | 0.1759 | 0.9334 |
| 0.0781 | 3.0 | 2346 | 0.3157 | 0.9292 |
| 0.0404 | 4.0 | 3128 | 0.3269 | 0.9353 |
| 0.0297 | 5.0 | 3910 | 0.3412 | 0.9358 |
| 0.0156 | 6.0 | 4692 | 0.3936 | 0.9356 |
| 0.011 | 7.0 | 5474 | 0.4316 | 0.9392 |
| 0.0054 | 8.0 | 6256 | 0.4882 | 0.9389 |
| 0.0019 | 9.0 | 7038 | 0.4972 | 0.9397 |
| 0.0011 | 10.0 | 7820 | 0.5157 | 0.9400 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0
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