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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_lr2e-05_seed42_basic_original_kin-hau-eng_train
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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_lr2e-05_seed42_basic_original_kin-hau-eng_train
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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: 0.0348
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+ - Spearman Corr: 0.7245
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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 | 1.59 | 200 | 0.0325 | 0.6966 |
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+ | 0.0428 | 3.19 | 400 | 0.0319 | 0.7262 |
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+ | 0.0237 | 4.78 | 600 | 0.0334 | 0.7202 |
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+ | 0.0178 | 6.37 | 800 | 0.0315 | 0.7350 |
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+ | 0.0138 | 7.97 | 1000 | 0.0339 | 0.7365 |
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+ | 0.0138 | 9.56 | 1200 | 0.0325 | 0.7316 |
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+ | 0.0107 | 11.16 | 1400 | 0.0354 | 0.7334 |
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+ | 0.0089 | 12.75 | 1600 | 0.0345 | 0.7268 |
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+ | 0.0075 | 14.34 | 1800 | 0.0346 | 0.7321 |
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+ | 0.0063 | 15.94 | 2000 | 0.0360 | 0.7278 |
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+ | 0.0063 | 17.53 | 2200 | 0.0384 | 0.7253 |
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+ | 0.0057 | 19.12 | 2400 | 0.0320 | 0.7226 |
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+ | 0.005 | 20.72 | 2600 | 0.0337 | 0.7213 |
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+ | 0.0047 | 22.31 | 2800 | 0.0348 | 0.7245 |
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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 2.1.0+cu121
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.2
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