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xlm-roberta-base_hau_corr_5e-06
Shijia/xlm-roberta-base_hau_corr_5e-06
xlm-roberta-base_hau_corr_5e-06 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
- e5995068
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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_hau_corr_5e-06
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: 0.0237
- Spearman Corr: 0.7615
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: 5e-06
- 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 | 0.95 | 200 | 0.0254 | 0.7574 |
| No log | 1.91 | 400 | 0.0249 | 0.7595 |
| 0.0025 | 2.86 | 600 | 0.0243 | 0.7626 |
| 0.0025 | 3.82 | 800 | 0.0251 | 0.7601 |
| 0.0023 | 4.77 | 1000 | 0.0241 | 0.7589 |
| 0.0023 | 5.73 | 1200 | 0.0236 | 0.7597 |
| 0.0023 | 6.68 | 1400 | 0.0243 | 0.7610 |
| 0.0023 | 7.64 | 1600 | 0.0251 | 0.7637 |
| 0.0022 | 8.59 | 1800 | 0.0251 | 0.7599 |
| 0.0022 | 9.55 | 2000 | 0.0255 | 0.7603 |
| 0.0021 | 10.5 | 2200 | 0.0252 | 0.7606 |
| 0.0021 | 11.46 | 2400 | 0.0244 | 0.7628 |
| 0.002 | 12.41 | 2600 | 0.0257 | 0.7644 |
| 0.002 | 13.37 | 2800 | 0.0250 | 0.7610 |
| 0.002 | 14.32 | 3000 | 0.0254 | 0.7600 |
| 0.002 | 15.27 | 3200 | 0.0250 | 0.7618 |
| 0.0019 | 16.23 | 3400 | 0.0249 | 0.7617 |
| 0.0019 | 17.18 | 3600 | 0.0247 | 0.7602 |
| 0.0019 | 18.14 | 3800 | 0.0245 | 0.7624 |
| 0.0019 | 19.09 | 4000 | 0.0244 | 0.7639 |
| 0.0018 | 20.05 | 4200 | 0.0237 | 0.7615 |
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