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xlm-roberta-ft-news-class2
reichenbach/xlm-roberta-ft-news-class2
xlm-roberta-ft-news-class2 is a text classification model from reichenbach. 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
- Aug 13, 2023
- Updated
- Aug 27, 2023
- SHA
- 23d4ddff
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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. -->
xlm-roberta-ft-news-class2
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8010
- Accuracy: 0.5115
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: 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 |
|---|---|---|---|---|
| 1.9938 | 1.0 | 10477 | 1.9427 | 0.4726 |
| 1.8313 | 2.0 | 20954 | 1.8492 | 0.4938 |
| 1.7042 | 3.0 | 31431 | 1.8031 | 0.5019 |
| 1.5338 | 4.0 | 41908 | 1.7811 | 0.5123 |
| 1.3984 | 5.0 | 52385 | 1.8010 | 0.5115 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Aug 13, 2023
- Updated
- Aug 27, 2023