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--- |
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base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48 |
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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-massive-intermediate_KD_new |
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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: 0.8165272995573045 |
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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-massive-intermediate_KD_new |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6631 |
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- Accuracy: 0.8165 |
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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: 50 |
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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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| 5.2865 | 1.0 | 180 | 4.1021 | 0.1692 | |
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| 4.1098 | 2.0 | 360 | 3.6293 | 0.2494 | |
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| 3.6635 | 3.0 | 540 | 3.1836 | 0.3665 | |
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| 3.311 | 4.0 | 720 | 2.9568 | 0.4555 | |
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| 3.0266 | 5.0 | 900 | 2.7684 | 0.4791 | |
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| 2.8087 | 6.0 | 1080 | 2.5803 | 0.5903 | |
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| 2.6276 | 7.0 | 1260 | 2.4481 | 0.6335 | |
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| 2.4728 | 8.0 | 1440 | 2.3491 | 0.6763 | |
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| 2.3497 | 9.0 | 1620 | 2.3474 | 0.6508 | |
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| 2.2557 | 10.0 | 1800 | 2.3618 | 0.6945 | |
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| 2.1673 | 11.0 | 1980 | 2.1769 | 0.7324 | |
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| 2.0929 | 12.0 | 2160 | 2.2181 | 0.7177 | |
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| 2.0125 | 13.0 | 2340 | 2.0942 | 0.7659 | |
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| 1.9507 | 14.0 | 2520 | 2.0009 | 0.7767 | |
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| 1.8811 | 15.0 | 2700 | 2.0316 | 0.7624 | |
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| 1.8356 | 16.0 | 2880 | 2.0107 | 0.7698 | |
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| 1.7935 | 17.0 | 3060 | 1.9687 | 0.7742 | |
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| 1.7436 | 18.0 | 3240 | 1.9601 | 0.7811 | |
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| 1.7158 | 19.0 | 3420 | 1.9357 | 0.7836 | |
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| 1.6848 | 20.0 | 3600 | 1.9413 | 0.7747 | |
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| 1.6421 | 21.0 | 3780 | 1.9428 | 0.7723 | |
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| 1.6091 | 22.0 | 3960 | 1.8787 | 0.7944 | |
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| 1.5758 | 23.0 | 4140 | 1.8953 | 0.7831 | |
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| 1.5557 | 24.0 | 4320 | 1.8503 | 0.7964 | |
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| 1.5249 | 25.0 | 4500 | 1.8481 | 0.7939 | |
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| 1.5082 | 26.0 | 4680 | 1.8342 | 0.7983 | |
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| 1.4827 | 27.0 | 4860 | 1.7922 | 0.7993 | |
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| 1.4552 | 28.0 | 5040 | 1.7805 | 0.7988 | |
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| 1.4296 | 29.0 | 5220 | 1.7730 | 0.7988 | |
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| 1.4067 | 30.0 | 5400 | 1.7724 | 0.7993 | |
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| 1.3843 | 31.0 | 5580 | 1.7438 | 0.8032 | |
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| 1.3721 | 32.0 | 5760 | 1.7842 | 0.7954 | |
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| 1.358 | 33.0 | 5940 | 1.7238 | 0.8087 | |
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| 1.3332 | 34.0 | 6120 | 1.6919 | 0.8091 | |
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| 1.3211 | 35.0 | 6300 | 1.7014 | 0.8042 | |
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| 1.3063 | 36.0 | 6480 | 1.6718 | 0.8131 | |
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| 1.2863 | 37.0 | 6660 | 1.6631 | 0.8165 | |
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| 1.2753 | 38.0 | 6840 | 1.6867 | 0.8091 | |
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| 1.2651 | 39.0 | 7020 | 1.6675 | 0.8067 | |
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| 1.2475 | 40.0 | 7200 | 1.6524 | 0.8072 | |
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| 1.2343 | 41.0 | 7380 | 1.6218 | 0.8165 | |
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| 1.2223 | 42.0 | 7560 | 1.6201 | 0.8155 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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