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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
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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: mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
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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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+ # mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
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+
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+ This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2718
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+ - F1 Macro: 0.9088
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+ - F1 Micro: 0.9089
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+ - Accuracy Balanced: 0.9089
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+ - Accuracy: 0.9089
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+ - Precision Macro: 0.9092
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+ - Recall Macro: 0.9089
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+ - Precision Micro: 0.9089
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+ - Recall Micro: 0.9089
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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: 16
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+ - eval_batch_size: 128
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+ - seed: 20241201
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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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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+ - lr_scheduler_warmup_ratio: 0.06
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
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+ | 0.2798 | 1.69 | 200 | 0.3328 | 0.8677 | 0.8677 | 0.8681 | 0.8677 | 0.8678 | 0.8681 | 0.8677 | 0.8677 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 2.14.7
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+ - Tokenizers 0.13.3
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