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xlmr-si-en-all_shuffled-1986-test2000
patpizio/xlmr-si-en-all_shuffled-1986-test2000
xlmr-si-en-all_shuffled-1986-test2000 is a text classification model from patpizio. 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
- Nov 23, 2023
- Updated
- Nov 23, 2023
- SHA
- cab15be0
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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. -->
xlmr-si-en-all_shuffled-1986-test2000
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7899
- R Squared: 0.0496
- Mae: 0.7124
- Pearson R: 0.5006
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: 16
- eval_batch_size: 16
- seed: 1986
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | R Squared | Mae | Pearson R |
|---|---|---|---|---|---|---|
| No log | 1.0 | 375 | 0.7236 | 0.1294 | 0.7195 | 0.4515 |
| 0.735 | 2.0 | 750 | 0.7800 | 0.0615 | 0.7121 | 0.4780 |
| 0.554 | 3.0 | 1125 | 0.7899 | 0.0496 | 0.7124 | 0.5006 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Nov 23, 2023
- Updated
- Nov 23, 2023