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results
zijuncheng/results
results is a text classification model from zijuncheng. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Aug 18, 2023
- Updated
- Aug 18, 2023
- SHA
- ae13e334
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Base models
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. -->
results
This model is a fine-tuned version of roberta-base on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2250
- Accuracy: 0.9133
- F1: 0.9161
- Precision: 0.8875
- Recall: 0.9467
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6922 | 0.98 | 46 | 0.6867 | 0.7433 | 0.6778 | 0.9101 | 0.54 |
| 0.2634 | 1.98 | 93 | 0.3428 | 0.8833 | 0.8736 | 0.9528 | 0.8067 |
| 0.1736 | 2.94 | 138 | 0.2250 | 0.9133 | 0.9161 | 0.8875 | 0.9467 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Aug 18, 2023
- Updated
- Aug 18, 2023