Model save
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- pytorch_model.bin +1 -1
README.md
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---
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license: mit
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base_model: xlm-roberta-base
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tags:
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- generated_from_trainer
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model-index:
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- name: xlmr-si-en-all_shuffled-2020-test1000
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# xlmr-si-en-all_shuffled-2020-test1000
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8030
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- R Squared: 0.0373
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- Mae: 0.7088
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- Pearson R: 0.5232
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 2020
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | R Squared | Mae | Pearson R |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:|
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| No log | 1.0 | 438 | 0.7537 | 0.0964 | 0.7613 | 0.3509 |
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| 0.8088 | 2.0 | 876 | 0.6291 | 0.2458 | 0.6462 | 0.5263 |
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| 0.6342 | 3.0 | 1314 | 0.8030 | 0.0373 | 0.7088 | 0.5232 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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pytorch_model.bin
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