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End of training

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+ ---
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+ license: mit
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+ base_model: FacebookAI/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: xlm-roberta-base_pan_loss_2e-05
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+ results: []
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+ ---
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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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+
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+ # xlm-roberta-base_pan_loss_2e-05
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+
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/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: 0.0216
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+ - Spearman Corr: 0.7776
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 128
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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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: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------:|
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+ | No log | 0.85 | 200 | 0.0210 | 0.7733 |
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+ | No log | 1.69 | 400 | 0.0215 | 0.7798 |
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+ | 0.0009 | 2.54 | 600 | 0.0219 | 0.7770 |
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+ | 0.0009 | 3.38 | 800 | 0.0212 | 0.7807 |
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+ | 0.0006 | 4.23 | 1000 | 0.0224 | 0.7806 |
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+ | 0.0006 | 5.07 | 1200 | 0.0210 | 0.7800 |
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+ | 0.0006 | 5.92 | 1400 | 0.0208 | 0.7799 |
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+ | 0.0004 | 6.77 | 1600 | 0.0214 | 0.7793 |
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+ | 0.0004 | 7.61 | 1800 | 0.0216 | 0.7795 |
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+ | 0.0003 | 8.46 | 2000 | 0.0207 | 0.7819 |
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+ | 0.0003 | 9.3 | 2200 | 0.0209 | 0.7826 |
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+ | 0.0004 | 10.15 | 2400 | 0.0209 | 0.7793 |
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+ | 0.0004 | 10.99 | 2600 | 0.0207 | 0.7804 |
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+ | 0.0004 | 11.84 | 2800 | 0.0210 | 0.7808 |
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+ | 0.0004 | 12.68 | 3000 | 0.0216 | 0.7776 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.2
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