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hBERTv2_new_pretrain_w_init__qnli
gokuls/hBERTv2_new_pretrain_w_init__qnli
hBERTv2_new_pretrain_w_init__qnli 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
- Jun 6, 2023
- Updated
- Jun 6, 2023
- SHA
- 83f2a2a8
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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. -->
hBERTv2_new_pretrain_w_init__qnli
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_wt_init on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6573
- Accuracy: 0.5958
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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- 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 |
|---|---|---|---|---|
| 0.6809 | 1.0 | 819 | 0.6640 | 0.6021 |
| 0.6539 | 2.0 | 1638 | 0.6573 | 0.5958 |
| 0.6358 | 3.0 | 2457 | 0.6694 | 0.5942 |
| 0.6313 | 4.0 | 3276 | 0.6898 | 0.5790 |
| 0.6293 | 5.0 | 4095 | 0.6801 | 0.5880 |
| 0.6253 | 6.0 | 4914 | 0.6829 | 0.5925 |
| 0.6166 | 7.0 | 5733 | 0.6865 | 0.5916 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- hybridbert
- Languages
- en
- Created
- Jun 6, 2023
- Updated
- Jun 6, 2023