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hbertv1-massive-logit_KD-small
gokuls/hbertv1-massive-logit_KD-small
hbertv1-massive-logit_KD-small is a text classification model from gokuls. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- hybridbert
- Access
- Public
- Created
- Nov 26, 2023
- Updated
- Nov 26, 2023
- SHA
- 0f584ba2
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Datasets
Model card
From the Hugging Face model README
<!-- 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-small
This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_small_freeze_new on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.4139
- Accuracy: 0.8736
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 |
|---|---|---|---|---|
| 2.2301 | 1.0 | 180 | 0.8611 | 0.7565 |
| 0.8039 | 2.0 | 360 | 0.5989 | 0.8151 |
| 0.5542 | 3.0 | 540 | 0.5036 | 0.8396 |
| 0.4134 | 4.0 | 720 | 0.4535 | 0.8569 |
| 0.3187 | 5.0 | 900 | 0.4432 | 0.8569 |
| 0.251 | 6.0 | 1080 | 0.4280 | 0.8637 |
| 0.2201 | 7.0 | 1260 | 0.4311 | 0.8598 |
| 0.1879 | 8.0 | 1440 | 0.4443 | 0.8608 |
| 0.168 | 9.0 | 1620 | 0.4136 | 0.8677 |
| 0.153 | 10.0 | 1800 | 0.4286 | 0.8598 |
| 0.137 | 11.0 | 1980 | 0.4148 | 0.8701 |
| 0.1276 | 12.0 | 2160 | 0.4158 | 0.8711 |
| 0.1196 | 13.0 | 2340 | 0.3975 | 0.8721 |
| 0.1137 | 14.0 | 2520 | 0.4221 | 0.8662 |
| 0.1066 | 15.0 | 2700 | 0.4085 | 0.8677 |
| 0.1024 | 16.0 | 2880 | 0.4048 | 0.8687 |
| 0.0995 | 17.0 | 3060 | 0.4139 | 0.8736 |
| 0.0949 | 18.0 | 3240 | 0.3953 | 0.8706 |
| 0.0908 | 19.0 | 3420 | 0.3984 | 0.8716 |
| 0.0882 | 20.0 | 3600 | 0.4006 | 0.8701 |
| 0.0864 | 21.0 | 3780 | 0.3943 | 0.8731 |
| 0.0837 | 22.0 | 3960 | 0.3912 | 0.8692 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- hybridbert
- Created
- Nov 26, 2023
- Updated
- Nov 26, 2023