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emotiscan_model_2
Mofe/emotiscan_model_2
emotiscan_model_2 is a text classification model from Mofe. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Mar 31, 2024
- Updated
- Apr 1, 2024
- SHA
- 583b1724
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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. -->
emotiscan_model_2
This model is a fine-tuned version of google-bert/bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5213
- Accuracy: 0.8184
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4986 | 1.0 | 4157 | 0.4979 | 0.8194 |
| 0.453 | 2.0 | 8315 | 0.4985 | 0.8200 |
| 0.4098 | 3.0 | 12471 | 0.5213 | 0.8184 |
Framework versions
- Transformers 4.29.0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 31, 2024
- Updated
- Apr 1, 2024