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hbertv1-massive-intermediate_KD_new

Text Classification
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hybridbert
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  1. README.md +116 -0
  2. logs/events.out.tfevents.1700963350.serv-3318.875323.0 +2 -2
  3. logs/events.out.tfevents.1700964239.serv-3318.875323.1 +3 -0
  4. model.safetensors +1 -1
README.md ADDED
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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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+
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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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+
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+ # hbertv1-massive-intermediate_KD_new
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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