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add_BERT_24_wnli
gokuls/add_BERT_24_wnli
add_BERT_24_wnli 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 16, 2023
- Updated
- Jun 16, 2023
- SHA
- 9eab72aa
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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_24_wnli
This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6832
- Accuracy: 0.5634
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 |
|---|---|---|---|---|
| 0.8485 | 1.0 | 5 | 0.8042 | 0.4366 |
| 0.7152 | 2.0 | 10 | 0.7515 | 0.4366 |
| 0.7134 | 3.0 | 15 | 0.6832 | 0.5634 |
| 0.7031 | 4.0 | 20 | 0.6854 | 0.5634 |
| 0.7007 | 5.0 | 25 | 0.6940 | 0.4789 |
| 0.7004 | 6.0 | 30 | 0.6940 | 0.4366 |
| 0.6968 | 7.0 | 35 | 0.6909 | 0.5070 |
| 0.7052 | 8.0 | 40 | 0.6903 | 0.5493 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- hybridbert
- Languages
- en
- Created
- Jun 16, 2023
- Updated
- Jun 16, 2023