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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: finetuned-self_mlm_small |
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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: 0.9372 |
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- name: F1 |
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type: f1 |
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value: 0.9675820772248607 |
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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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# finetuned-self_mlm_small |
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This model is a fine-tuned version of [muhtasham/bert-small-mlm-finetuned-imdb](https://huggingface.co/muhtasham/bert-small-mlm-finetuned-imdb) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3759 |
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- Accuracy: 0.9372 |
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- F1: 0.9676 |
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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: 64 |
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- eval_batch_size: 64 |
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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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| 0.2834 | 1.28 | 500 | 0.2254 | 0.9150 | 0.9556 | |
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| 0.1683 | 2.56 | 1000 | 0.3738 | 0.8694 | 0.9301 | |
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| 0.1069 | 3.84 | 1500 | 0.2102 | 0.9354 | 0.9666 | |
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| 0.0651 | 5.12 | 2000 | 0.2278 | 0.9446 | 0.9715 | |
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| 0.0412 | 6.39 | 2500 | 0.4061 | 0.9156 | 0.9559 | |
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| 0.0316 | 7.67 | 3000 | 0.4371 | 0.9110 | 0.9534 | |
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| 0.0219 | 8.95 | 3500 | 0.3759 | 0.9372 | 0.9676 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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