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---
base_model: gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: hbertv1-massive-logit_KD-tiny_ffn_0.5
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: 0.8407919331037875
---
<!-- 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-logit_KD-tiny_ffn_0.5
This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6585
- Accuracy: 0.8308
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3023 | 1.0 | 180 | 3.8354 | 0.1766 |
| 3.7037 | 2.0 | 360 | 3.2686 | 0.2027 |
| 3.2011 | 3.0 | 540 | 2.8012 | 0.2966 |
| 2.774 | 4.0 | 720 | 2.4055 | 0.3802 |
| 2.4069 | 5.0 | 900 | 2.0833 | 0.4747 |
| 2.1164 | 6.0 | 1080 | 1.8300 | 0.5588 |
| 1.8907 | 7.0 | 1260 | 1.6351 | 0.6252 |
| 1.71 | 8.0 | 1440 | 1.4792 | 0.6621 |
| 1.5648 | 9.0 | 1620 | 1.3605 | 0.6936 |
| 1.4399 | 10.0 | 1800 | 1.2607 | 0.7103 |
| 1.3436 | 11.0 | 1980 | 1.1872 | 0.7201 |
| 1.266 | 12.0 | 2160 | 1.1295 | 0.7285 |
| 1.1934 | 13.0 | 2340 | 1.0829 | 0.7359 |
| 1.1413 | 14.0 | 2520 | 1.0428 | 0.7472 |
| 1.0807 | 15.0 | 2700 | 0.9984 | 0.7585 |
| 1.0382 | 16.0 | 2880 | 0.9693 | 0.7600 |
| 0.9982 | 17.0 | 3060 | 0.9439 | 0.7673 |
| 0.9626 | 18.0 | 3240 | 0.9207 | 0.7723 |
| 0.9299 | 19.0 | 3420 | 0.8887 | 0.7796 |
| 0.8828 | 20.0 | 3600 | 0.8686 | 0.7796 |
| 0.8593 | 21.0 | 3780 | 0.8537 | 0.7905 |
| 0.8329 | 22.0 | 3960 | 0.8250 | 0.7934 |
| 0.8043 | 23.0 | 4140 | 0.8098 | 0.7959 |
| 0.7764 | 24.0 | 4320 | 0.7990 | 0.8008 |
| 0.7569 | 25.0 | 4500 | 0.7823 | 0.8067 |
| 0.7372 | 26.0 | 4680 | 0.7749 | 0.8023 |
| 0.7182 | 27.0 | 4860 | 0.7640 | 0.8101 |
| 0.6987 | 28.0 | 5040 | 0.7509 | 0.8106 |
| 0.6842 | 29.0 | 5220 | 0.7386 | 0.8146 |
| 0.6673 | 30.0 | 5400 | 0.7305 | 0.8146 |
| 0.6509 | 31.0 | 5580 | 0.7196 | 0.8214 |
| 0.6382 | 32.0 | 5760 | 0.7120 | 0.8170 |
| 0.6301 | 33.0 | 5940 | 0.7134 | 0.8190 |
| 0.6139 | 34.0 | 6120 | 0.7062 | 0.8200 |
| 0.6076 | 35.0 | 6300 | 0.6928 | 0.8205 |
| 0.5919 | 36.0 | 6480 | 0.6838 | 0.8244 |
| 0.5792 | 37.0 | 6660 | 0.6819 | 0.8264 |
| 0.5739 | 38.0 | 6840 | 0.6780 | 0.8210 |
| 0.5698 | 39.0 | 7020 | 0.6684 | 0.8283 |
| 0.5602 | 40.0 | 7200 | 0.6692 | 0.8249 |
| 0.5534 | 41.0 | 7380 | 0.6644 | 0.8298 |
| 0.5429 | 42.0 | 7560 | 0.6599 | 0.8278 |
| 0.5423 | 43.0 | 7740 | 0.6585 | 0.8308 |
| 0.5356 | 44.0 | 7920 | 0.6569 | 0.8293 |
| 0.5374 | 45.0 | 8100 | 0.6565 | 0.8293 |
| 0.5327 | 46.0 | 8280 | 0.6540 | 0.8273 |
| 0.5324 | 47.0 | 8460 | 0.6523 | 0.8273 |
| 0.5281 | 48.0 | 8640 | 0.6519 | 0.8283 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0
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