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xlm-roberta-base_esp_corr_2e-05
Shijia/xlm-roberta-base_esp_corr_2e-05
xlm-roberta-base_esp_corr_2e-05 is a text classification model from Shijia. 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
- Feb 17, 2024
- Updated
- Feb 17, 2024
- SHA
- 6ce8f062
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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-base_esp_corr_2e-05
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0215
- Spearman Corr: 0.7827
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: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|---|---|---|---|---|
| No log | 0.94 | 200 | 0.0216 | 0.7772 |
| No log | 1.89 | 400 | 0.0220 | 0.7787 |
| 0.001 | 2.83 | 600 | 0.0229 | 0.7785 |
| 0.001 | 3.77 | 800 | 0.0229 | 0.7756 |
| 0.001 | 4.72 | 1000 | 0.0222 | 0.7790 |
| 0.001 | 5.66 | 1200 | 0.0210 | 0.7827 |
| 0.0009 | 6.6 | 1400 | 0.0222 | 0.7784 |
| 0.0009 | 7.55 | 1600 | 0.0214 | 0.7788 |
| 0.0008 | 8.49 | 1800 | 0.0227 | 0.7798 |
| 0.0008 | 9.43 | 2000 | 0.0218 | 0.7792 |
| 0.0008 | 10.38 | 2200 | 0.0215 | 0.7804 |
| 0.0008 | 11.32 | 2400 | 0.0208 | 0.7798 |
| 0.0007 | 12.26 | 2600 | 0.0220 | 0.7833 |
| 0.0007 | 13.21 | 2800 | 0.0209 | 0.7820 |
| 0.0007 | 14.15 | 3000 | 0.0212 | 0.7833 |
| 0.0007 | 15.09 | 3200 | 0.0213 | 0.7800 |
| 0.0006 | 16.04 | 3400 | 0.0215 | 0.7810 |
| 0.0006 | 16.98 | 3600 | 0.0221 | 0.7811 |
| 0.0006 | 17.92 | 3800 | 0.0215 | 0.7813 |
| 0.0006 | 18.87 | 4000 | 0.0216 | 0.7822 |
| 0.0006 | 19.81 | 4200 | 0.0215 | 0.7827 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Feb 17, 2024
- Updated
- Feb 17, 2024