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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/xlm-roberta-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: xlmr_immigration_combo26_1 |
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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_immigration_combo26_1 |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2140 |
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- Accuracy: 0.9344 |
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- 1-f1: 0.9006 |
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- 1-recall: 0.8919 |
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- 1-precision: 0.9094 |
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- Balanced Acc: 0.9238 |
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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: 1e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
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| 0.2591 | 1.0 | 25 | 0.1775 | 0.9409 | 0.9073 | 0.8687 | 0.9494 | 0.9228 | |
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| 0.2407 | 2.0 | 50 | 0.1862 | 0.9280 | 0.8862 | 0.8417 | 0.9356 | 0.9064 | |
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| 0.1988 | 3.0 | 75 | 0.2140 | 0.9344 | 0.9006 | 0.8919 | 0.9094 | 0.9238 | |
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### Framework versions |
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- Transformers 4.56.0.dev0 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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