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--- |
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base_model: gokuls/HBERTv1_48_L4_H768_A12 |
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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_L4_H768_A12_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: 0.8726020659124447 |
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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_L4_H768_A12_massive |
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This model is a fine-tuned version of [gokuls/HBERTv1_48_L4_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L4_H768_A12) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7904 |
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- Accuracy: 0.8726 |
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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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| 1.714 | 1.0 | 180 | 0.7757 | 0.7826 | |
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| 0.6529 | 2.0 | 360 | 0.6221 | 0.8328 | |
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| 0.4238 | 3.0 | 540 | 0.5757 | 0.8544 | |
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| 0.2832 | 4.0 | 720 | 0.5940 | 0.8544 | |
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| 0.2056 | 5.0 | 900 | 0.6066 | 0.8495 | |
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| 0.1417 | 6.0 | 1080 | 0.6677 | 0.8559 | |
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| 0.0983 | 7.0 | 1260 | 0.6791 | 0.8519 | |
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| 0.0741 | 8.0 | 1440 | 0.7092 | 0.8495 | |
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| 0.0495 | 9.0 | 1620 | 0.7061 | 0.8687 | |
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| 0.0356 | 10.0 | 1800 | 0.7682 | 0.8633 | |
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| 0.0243 | 11.0 | 1980 | 0.7785 | 0.8623 | |
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| 0.0144 | 12.0 | 2160 | 0.7833 | 0.8677 | |
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| 0.0099 | 13.0 | 2340 | 0.7941 | 0.8711 | |
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| 0.0063 | 14.0 | 2520 | 0.7904 | 0.8726 | |
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| 0.0037 | 15.0 | 2700 | 0.8014 | 0.8677 | |
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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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