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--- |
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license: openrail |
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base_model: versae/gzip-bert |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imdb |
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metrics: |
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- accuracy |
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model-index: |
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- name: gzipbert_imdb_rpe_250k |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: imdb |
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type: imdb |
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config: plain_text |
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split: test |
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args: plain_text |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.50952 |
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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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# gzipbert_imdb_rpe_250k |
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This model is a fine-tuned version of [versae/gzip-bert](https://huggingface.co/versae/gzip-bert) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.0866 |
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- Accuracy: 0.5095 |
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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-06 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.003 | 1.0 | 1563 | 5.1727 | 0.5548 | |
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| 0.0061 | 2.0 | 3126 | 5.7975 | 0.5176 | |
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| 0.0056 | 3.0 | 4689 | 5.6762 | 0.5107 | |
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| 0.0019 | 4.0 | 6252 | 6.0355 | 0.5082 | |
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| 0.0043 | 5.0 | 7815 | 6.0866 | 0.5095 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.0 |
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- Tokenizers 0.13.3 |
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