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---
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: hbertv1-massive-intermediate_KD_new
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive
config: en-US
split: validation
args: en-US
metrics:
- name: Accuracy
type: accuracy
value: 0.8165272995573045
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hbertv1-massive-intermediate_KD_new
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.
It achieves the following results on the evaluation set:
- Loss: 1.6631
- Accuracy: 0.8165
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.2865 | 1.0 | 180 | 4.1021 | 0.1692 |
| 4.1098 | 2.0 | 360 | 3.6293 | 0.2494 |
| 3.6635 | 3.0 | 540 | 3.1836 | 0.3665 |
| 3.311 | 4.0 | 720 | 2.9568 | 0.4555 |
| 3.0266 | 5.0 | 900 | 2.7684 | 0.4791 |
| 2.8087 | 6.0 | 1080 | 2.5803 | 0.5903 |
| 2.6276 | 7.0 | 1260 | 2.4481 | 0.6335 |
| 2.4728 | 8.0 | 1440 | 2.3491 | 0.6763 |
| 2.3497 | 9.0 | 1620 | 2.3474 | 0.6508 |
| 2.2557 | 10.0 | 1800 | 2.3618 | 0.6945 |
| 2.1673 | 11.0 | 1980 | 2.1769 | 0.7324 |
| 2.0929 | 12.0 | 2160 | 2.2181 | 0.7177 |
| 2.0125 | 13.0 | 2340 | 2.0942 | 0.7659 |
| 1.9507 | 14.0 | 2520 | 2.0009 | 0.7767 |
| 1.8811 | 15.0 | 2700 | 2.0316 | 0.7624 |
| 1.8356 | 16.0 | 2880 | 2.0107 | 0.7698 |
| 1.7935 | 17.0 | 3060 | 1.9687 | 0.7742 |
| 1.7436 | 18.0 | 3240 | 1.9601 | 0.7811 |
| 1.7158 | 19.0 | 3420 | 1.9357 | 0.7836 |
| 1.6848 | 20.0 | 3600 | 1.9413 | 0.7747 |
| 1.6421 | 21.0 | 3780 | 1.9428 | 0.7723 |
| 1.6091 | 22.0 | 3960 | 1.8787 | 0.7944 |
| 1.5758 | 23.0 | 4140 | 1.8953 | 0.7831 |
| 1.5557 | 24.0 | 4320 | 1.8503 | 0.7964 |
| 1.5249 | 25.0 | 4500 | 1.8481 | 0.7939 |
| 1.5082 | 26.0 | 4680 | 1.8342 | 0.7983 |
| 1.4827 | 27.0 | 4860 | 1.7922 | 0.7993 |
| 1.4552 | 28.0 | 5040 | 1.7805 | 0.7988 |
| 1.4296 | 29.0 | 5220 | 1.7730 | 0.7988 |
| 1.4067 | 30.0 | 5400 | 1.7724 | 0.7993 |
| 1.3843 | 31.0 | 5580 | 1.7438 | 0.8032 |
| 1.3721 | 32.0 | 5760 | 1.7842 | 0.7954 |
| 1.358 | 33.0 | 5940 | 1.7238 | 0.8087 |
| 1.3332 | 34.0 | 6120 | 1.6919 | 0.8091 |
| 1.3211 | 35.0 | 6300 | 1.7014 | 0.8042 |
| 1.3063 | 36.0 | 6480 | 1.6718 | 0.8131 |
| 1.2863 | 37.0 | 6660 | 1.6631 | 0.8165 |
| 1.2753 | 38.0 | 6840 | 1.6867 | 0.8091 |
| 1.2651 | 39.0 | 7020 | 1.6675 | 0.8067 |
| 1.2475 | 40.0 | 7200 | 1.6524 | 0.8072 |
| 1.2343 | 41.0 | 7380 | 1.6218 | 0.8165 |
| 1.2223 | 42.0 | 7560 | 1.6201 | 0.8155 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0
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