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--- |
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base_model: gokuls/HBERTv1_48_L8_H512_A8 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- massive |
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metrics: |
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- accuracy |
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model-index: |
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- name: HBERTv1_48_L8_H512_A8_massive |
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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: massive |
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type: massive |
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config: en-US |
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split: validation |
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args: en-US |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8568617806197737 |
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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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# HBERTv1_48_L8_H512_A8_massive |
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This model is a fine-tuned version of [gokuls/HBERTv1_48_L8_H512_A8](https://huggingface.co/gokuls/HBERTv1_48_L8_H512_A8) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8009 |
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- Accuracy: 0.8569 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 33 |
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- distributed_type: multi-GPU |
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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: 15 |
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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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| 3.2383 | 1.0 | 180 | 2.0110 | 0.4747 | |
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| 1.5051 | 2.0 | 360 | 1.0904 | 0.7093 | |
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| 0.8998 | 3.0 | 540 | 0.8544 | 0.7727 | |
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| 0.661 | 4.0 | 720 | 0.7029 | 0.8160 | |
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| 0.5052 | 5.0 | 900 | 0.6987 | 0.8131 | |
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| 0.3889 | 6.0 | 1080 | 0.6901 | 0.8244 | |
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| 0.3062 | 7.0 | 1260 | 0.6746 | 0.8352 | |
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| 0.2422 | 8.0 | 1440 | 0.6946 | 0.8396 | |
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| 0.1834 | 9.0 | 1620 | 0.7290 | 0.8441 | |
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| 0.1402 | 10.0 | 1800 | 0.7416 | 0.8406 | |
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| 0.1098 | 11.0 | 1980 | 0.7828 | 0.8387 | |
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| 0.0803 | 12.0 | 2160 | 0.7700 | 0.8460 | |
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| 0.0612 | 13.0 | 2340 | 0.7891 | 0.8515 | |
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| 0.0468 | 14.0 | 2520 | 0.8009 | 0.8569 | |
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| 0.0375 | 15.0 | 2700 | 0.8032 | 0.8569 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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