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xlm-roberta-base_esp-kin-eng_train_spearman_corr
shanhy/xlm-roberta-base_esp-kin-eng_train_spearman_corr
xlm-roberta-base_esp-kin-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
- 610bd4f4
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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-kin-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: 0.0306
- Spearman Corr: 0.6931
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 | 0.54 | 200 | 0.0281 | 0.6201 |
| No log | 1.09 | 400 | 0.0245 | 0.6554 |
| No log | 1.63 | 600 | 0.0287 | 0.6675 |
| 0.0336 | 2.18 | 800 | 0.0326 | 0.6610 |
| 0.0336 | 2.72 | 1000 | 0.0292 | 0.6750 |
| 0.0336 | 3.27 | 1200 | 0.0294 | 0.6797 |
| 0.0336 | 3.81 | 1400 | 0.0276 | 0.6976 |
| 0.0203 | 4.35 | 1600 | 0.0276 | 0.7022 |
| 0.0203 | 4.9 | 1800 | 0.0259 | 0.6997 |
| 0.0203 | 5.44 | 2000 | 0.0283 | 0.7034 |
| 0.0203 | 5.99 | 2200 | 0.0279 | 0.7174 |
| 0.0146 | 6.53 | 2400 | 0.0310 | 0.6980 |
| 0.0146 | 7.07 | 2600 | 0.0303 | 0.6995 |
| 0.0146 | 7.62 | 2800 | 0.0285 | 0.6961 |
| 0.0105 | 8.16 | 3000 | 0.0372 | 0.6989 |
| 0.0105 | 8.71 | 3200 | 0.0284 | 0.6933 |
| 0.0105 | 9.25 | 3400 | 0.0351 | 0.7014 |
| 0.0105 | 9.8 | 3600 | 0.0331 | 0.7006 |
| 0.008 | 10.34 | 3800 | 0.0306 | 0.6931 |
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