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xlmr
joohwan/xlmr
xlmr is a text classification model from joohwan. 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 27, 2023
- Updated
- Jun 27, 2023
- SHA
- f5a81b54
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. -->
xlmr
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6138
- Accuracy: 0.9163
- F1: 0.9153
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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 | F1 |
|---|---|---|---|---|---|
| 0.3962 | 1.0 | 450 | 0.3872 | 0.9011 | 0.9005 |
| 0.0584 | 2.0 | 900 | 0.4941 | 0.9180 | 0.9171 |
| 0.0284 | 3.0 | 1350 | 0.6192 | 0.9138 | 0.9127 |
| 0.0144 | 4.0 | 1800 | 0.5967 | 0.9224 | 0.9214 |
| 0.0103 | 5.0 | 2250 | 0.6138 | 0.9163 | 0.9153 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jun 27, 2023
- Updated
- Jun 27, 2023