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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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datasets: |
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- imdb |
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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: base-vanilla-target-imdb |
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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: train |
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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: 0.9604 |
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- name: F1 |
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type: f1 |
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value: 0.9798000408079984 |
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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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# base-vanilla-target-imdb |
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This model is a fine-tuned version of [google/bert_uncased_L-12_H-768_A-12](https://huggingface.co/google/bert_uncased_L-12_H-768_A-12) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1564 |
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- Accuracy: 0.9604 |
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- F1: 0.9798 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: constant |
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- num_epochs: 200 |
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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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| 0.2549 | 0.64 | 500 | 0.2049 | 0.9234 | 0.9602 | |
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| 0.1771 | 1.28 | 1000 | 0.0750 | 0.9763 | 0.9880 | |
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| 0.1271 | 1.92 | 1500 | 0.0871 | 0.9707 | 0.9851 | |
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| 0.0755 | 2.56 | 2000 | 0.3361 | 0.9235 | 0.9602 | |
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| 0.0631 | 3.2 | 2500 | 0.1564 | 0.9604 | 0.9798 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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