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Malay-Sentiment3
afiqlol/Malay-Sentiment3
Malay-Sentiment3 is a text classification model from afiqlol. 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
- xlm-roberta
- Access
- Public
- Created
- May 21, 2024
- Updated
- May 21, 2024
- SHA
- 18628a2e
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Base models
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. -->
Malay-Sentiment3
This model is a fine-tuned version of citizenlab/twitter-xlm-roberta-base-sentiment-finetunned on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7976
- Accuracy: 0.7696
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.713 | 1.0 | 723 | 0.5733 | 0.7633 |
| 0.5687 | 2.0 | 1446 | 0.5964 | 0.7640 |
| 0.3369 | 3.0 | 2169 | 0.6799 | 0.7737 |
| 0.2823 | 4.0 | 2892 | 0.7976 | 0.7696 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cpu
- Datasets 2.14.5
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- May 21, 2024
- Updated
- May 21, 2024