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xlm-roberta-base-lowercase-high-accuracy
tukhtashevshohruh/xlm-roberta-base-lowercase-high-accuracy
xlm-roberta-base-lowercase-high-accuracy is a token classification model from tukhtashevshohruh. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
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: 0.16673 - Precision: 0.5710 - Recall: 0.6137 - F1: 0.5916
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 11, 2025
- Updated
- Mar 11, 2025
- SHA
- 53ba5ade
Base models
Model card
From the Hugging Face model README
xlm-roberta-base-lowercase
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: 0.16673
- Precision: 0.5710
- Recall: 0.6137
- F1: 0.5916
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.1949 | 1.0 | 2206 | 0.1788 | 0.5315 | 0.5391 | 0.5353 |
| 0.1669 | 2.0 | 4412 | 0.1670 | 0.5353 | 0.5995 | 0.5656 |
| 0.1361 | 3.0 | 6618 | 0.1667 | 0.5710 | 0.6137 | 0.5916 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Languages
- uz
- Created
- Mar 11, 2025
- Updated
- Mar 11, 2025