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hbertv1-emotion_48
gokuls/hbertv1-emotion_48
hbertv1-emotion_48 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 21, 2023
- Updated
- Jun 21, 2023
- SHA
- c3d69292
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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-emotion_48
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.3772
- Accuracy: 0.8815
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2197 | 1.0 | 250 | 0.9299 | 0.6805 |
| 0.7179 | 2.0 | 500 | 0.7201 | 0.771 |
| 0.5662 | 3.0 | 750 | 0.5293 | 0.839 |
| 0.4104 | 4.0 | 1000 | 0.4532 | 0.871 |
| 0.3445 | 5.0 | 1250 | 0.4412 | 0.8755 |
| 0.296 | 6.0 | 1500 | 0.3830 | 0.8735 |
| 0.2519 | 7.0 | 1750 | 0.3772 | 0.8815 |
| 0.2216 | 8.0 | 2000 | 0.3795 | 0.879 |
| 0.191 | 9.0 | 2250 | 0.3962 | 0.8775 |
| 0.1711 | 10.0 | 2500 | 0.3890 | 0.8775 |
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
- Created
- Jun 21, 2023
- Updated
- Jun 21, 2023