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xlm-roberta-base_original_amh-esp-eng_train_spearman_corr
shanhy/xlm-roberta-base_original_amh-esp-eng_train_spearman_corr
xlm-roberta-base_original_amh-esp-eng_train_spearman_corr is a text classification model from shanhy. 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 16, 2024
- Updated
- Feb 16, 2024
- SHA
- bdc0b217
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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_original_amh-esp-eng_train_spearman_corr
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: 0.0266
- Spearman Corr: 0.7569
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 | 1.59 | 200 | 0.0190 | 0.7396 |
| 0.0367 | 3.17 | 400 | 0.0185 | 0.7620 |
| 0.0198 | 4.76 | 600 | 0.0210 | 0.7633 |
| 0.0151 | 6.35 | 800 | 0.0206 | 0.7619 |
| 0.0151 | 7.94 | 1000 | 0.0320 | 0.7572 |
| 0.0117 | 9.52 | 1200 | 0.0284 | 0.7567 |
| 0.0089 | 11.11 | 1400 | 0.0263 | 0.7563 |
| 0.0073 | 12.7 | 1600 | 0.0255 | 0.7521 |
| 0.0059 | 14.29 | 1800 | 0.0254 | 0.7518 |
| 0.0059 | 15.87 | 2000 | 0.0265 | 0.7530 |
| 0.0051 | 17.46 | 2200 | 0.0266 | 0.7569 |
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 16, 2024
- Updated
- Feb 16, 2024