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xlm-roberta-base-finetuned
Tengisbold/xlm-roberta-base-finetuned
xlm-roberta-base-finetuned is a text classification model from Tengisbold. 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
- Apr 5, 2023
- Updated
- Apr 5, 2023
- SHA
- 6d39005c
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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. -->
xlm-roberta-base-finetuned
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: 1.7914
- Accuracy: 0.1667
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: 12
- eval_batch_size: 12
- 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 |
|---|---|---|---|---|
| 1.8324 | 1.0 | 10 | 1.7914 | 0.1667 |
| 1.7471 | 2.0 | 20 | 1.7462 | 0.1667 |
| 1.4988 | 3.0 | 30 | 1.5929 | 0.1667 |
| 1.5468 | 4.0 | 40 | 1.4534 | 0.1583 |
| 1.2911 | 5.0 | 50 | 1.4256 | 0.1583 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Apr 5, 2023
- Updated
- Apr 5, 2023