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--- |
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base_model: gokuls/HBERTv1_48_L12_H768_A12 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: HBERTv1_48_L12_H768_A12_massive_data_augmented |
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results: [] |
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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_L12_H768_A12_massive_data_augmented |
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This model is a fine-tuned version of [gokuls/HBERTv1_48_L12_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L12_H768_A12) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6902 |
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- Accuracy: 0.8377 |
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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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| 1.0914 | 1.0 | 4000 | 0.6902 | 0.8377 | |
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| 0.6178 | 2.0 | 8000 | 0.6890 | 0.8283 | |
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| 0.463 | 3.0 | 12000 | 0.7721 | 0.8254 | |
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| 0.3683 | 4.0 | 16000 | 0.7829 | 0.8288 | |
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| 0.3005 | 5.0 | 20000 | 0.8556 | 0.8303 | |
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| 0.2502 | 6.0 | 24000 | 0.9171 | 0.8214 | |
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| 0.2106 | 7.0 | 28000 | 1.0074 | 0.8160 | |
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| 0.1779 | 8.0 | 32000 | 1.0923 | 0.8239 | |
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| 0.1506 | 9.0 | 36000 | 1.1525 | 0.8254 | |
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| 0.1259 | 10.0 | 40000 | 1.2103 | 0.8249 | |
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| 0.1059 | 11.0 | 44000 | 1.3093 | 0.8269 | |
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| 0.0894 | 12.0 | 48000 | 1.4000 | 0.8288 | |
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| 0.0745 | 13.0 | 52000 | 1.5050 | 0.8313 | |
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| 0.0624 | 14.0 | 56000 | 1.5424 | 0.8288 | |
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| 0.0521 | 15.0 | 60000 | 1.5973 | 0.8308 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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