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fedcsis-intent_baseline-xlm_r-pl
Glorciocon3/fedcsis-intent_baseline-xlm_r-pl
fedcsis-intent_baseline-xlm_r-pl is a text classification model from Glorciocon3. 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 10, 2023
- Updated
- Jun 12, 2023
- SHA
- 5083aa5d
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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. -->
fedcsis-intent_baseline-xlm_r-pl
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: 0.2781
- Accuracy: 0.9389
- F1: 0.9389
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.5554 | 1.0 | 1275 | 0.9207 | 0.7954 | 0.7954 |
| 0.5204 | 2.0 | 2551 | 0.4151 | 0.9116 | 0.9116 |
| 0.2982 | 3.0 | 3827 | 0.2462 | 0.9496 | 0.9496 |
| 0.1767 | 4.0 | 5103 | 0.1827 | 0.9652 | 0.9652 |
| 0.1351 | 5.0 | 6375 | 0.1666 | 0.9661 | 0.9661 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jun 10, 2023
- Updated
- Jun 12, 2023