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add_BERT_no_pretrain_qnli
gokuls/add_BERT_no_pretrain_qnli
add_BERT_no_pretrain_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
- May 29, 2023
- Updated
- Jun 14, 2023
- SHA
- 80803c3a
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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. -->
add_BERT_no_pretrain_qnli
This model is a fine-tuned version of on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6899
- Accuracy: 0.5288
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 |
|---|---|---|---|---|
| 0.7079 | 1.0 | 819 | 0.7210 | 0.5054 |
| 0.6952 | 2.0 | 1638 | 0.6912 | 0.4946 |
| 0.6922 | 3.0 | 2457 | 0.6905 | 0.5279 |
| 0.6918 | 4.0 | 3276 | 0.6899 | 0.5288 |
| 0.6922 | 5.0 | 4095 | 0.6922 | 0.5153 |
| 0.6933 | 6.0 | 4914 | 0.6926 | 0.5127 |
| 0.6931 | 7.0 | 5733 | 0.6952 | 0.4946 |
| 0.6933 | 8.0 | 6552 | 0.6928 | 0.5113 |
| 0.693 | 9.0 | 7371 | 0.6922 | 0.5215 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- hybridbert
- Languages
- en
- Created
- May 29, 2023
- Updated
- Jun 14, 2023