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bookmebus-sentiment-analysis
seanghay/bookmebus-sentiment-analysis
bookmebus-sentiment-analysis is a text classification model from seanghay. 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
- xlm-roberta
- Access
- Public
- Created
- Jun 8, 2023
- Updated
- Jun 8, 2023
- SHA
- 56994ee6
Try a prompt
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. -->
bookmebus-roberta-2
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1144
- Accuracy: 0.5
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 249 | 1.2029 | 0.4931 |
| No log | 2.0 | 498 | 1.3241 | 0.5347 |
| 0.9919 | 3.0 | 747 | 1.3590 | 0.5 |
| 0.9919 | 4.0 | 996 | 1.4430 | 0.5139 |
| 0.7674 | 5.0 | 1245 | 1.5039 | 0.5486 |
| 0.7674 | 6.0 | 1494 | 1.6894 | 0.5208 |
| 0.5381 | 7.0 | 1743 | 1.9312 | 0.4861 |
| 0.5381 | 8.0 | 1992 | 1.9636 | 0.5208 |
| 0.3594 | 9.0 | 2241 | 2.0836 | 0.5 |
| 0.3594 | 10.0 | 2490 | 2.1144 | 0.5 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jun 8, 2023
- Updated
- Jun 8, 2023