End of training
Browse files- README.md +85 -0
- pytorch_model.bin +1 -1
README.md
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---
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base_model: 61347023S/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.1
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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-zeroshot-v1.2
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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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# mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.2
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This model is a fine-tuned version of [61347023S/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.1](https://huggingface.co/61347023S/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7018
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- F1 Macro: 0.8729
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- F1 Micro: 0.8745
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- Accuracy Balanced: 0.8716
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- Accuracy: 0.8745
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- Precision Macro: 0.8748
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- Recall Macro: 0.8716
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- Precision Micro: 0.8745
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- Recall Micro: 0.8745
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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: 128
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- seed: 35
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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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### Training results
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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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| 0.0962 | 0.17 | 200 | 0.5626 | 0.8709 | 0.8719 | 0.8714 | 0.8719 | 0.8704 | 0.8714 | 0.8719 | 0.8719 |
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| 0.1218 | 0.34 | 400 | 0.5258 | 0.8635 | 0.8650 | 0.8629 | 0.8650 | 0.8643 | 0.8629 | 0.8650 | 0.8650 |
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| 0.1246 | 0.51 | 600 | 0.4964 | 0.8652 | 0.8671 | 0.8635 | 0.8671 | 0.8679 | 0.8635 | 0.8671 | 0.8671 |
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| 0.1225 | 0.68 | 800 | 0.5676 | 0.8618 | 0.8629 | 0.8623 | 0.8629 | 0.8614 | 0.8623 | 0.8629 | 0.8629 |
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| 0.1429 | 0.85 | 1000 | 0.4402 | 0.8651 | 0.8666 | 0.8643 | 0.8666 | 0.8660 | 0.8643 | 0.8666 | 0.8666 |
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| 0.1129 | 1.02 | 1200 | 0.5230 | 0.8688 | 0.8703 | 0.8679 | 0.8703 | 0.8699 | 0.8679 | 0.8703 | 0.8703 |
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| 0.0921 | 1.19 | 1400 | 0.6435 | 0.8503 | 0.8534 | 0.8473 | 0.8534 | 0.8574 | 0.8473 | 0.8534 | 0.8534 |
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| 0.0972 | 1.35 | 1600 | 0.5313 | 0.8635 | 0.8650 | 0.8628 | 0.8650 | 0.8644 | 0.8628 | 0.8650 | 0.8650 |
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| 0.0883 | 1.52 | 1800 | 0.6088 | 0.8682 | 0.8692 | 0.8688 | 0.8692 | 0.8678 | 0.8688 | 0.8692 | 0.8692 |
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| 0.0985 | 1.69 | 2000 | 0.5890 | 0.8696 | 0.8708 | 0.8693 | 0.8708 | 0.8698 | 0.8693 | 0.8708 | 0.8708 |
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| 0.0838 | 1.86 | 2200 | 0.6647 | 0.8634 | 0.8650 | 0.8626 | 0.8650 | 0.8645 | 0.8626 | 0.8650 | 0.8650 |
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| 0.0703 | 2.03 | 2400 | 0.6527 | 0.8712 | 0.8729 | 0.8699 | 0.8729 | 0.8732 | 0.8699 | 0.8729 | 0.8729 |
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| 0.0639 | 2.2 | 2600 | 0.6665 | 0.8695 | 0.8714 | 0.8680 | 0.8714 | 0.8720 | 0.8680 | 0.8714 | 0.8714 |
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| 0.059 | 2.37 | 2800 | 0.7361 | 0.8668 | 0.8687 | 0.8650 | 0.8687 | 0.8696 | 0.8650 | 0.8687 | 0.8687 |
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| 0.062 | 2.54 | 3000 | 0.6719 | 0.8742 | 0.8756 | 0.8735 | 0.8756 | 0.8751 | 0.8735 | 0.8756 | 0.8756 |
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| 0.0419 | 2.71 | 3200 | 0.7057 | 0.8734 | 0.8751 | 0.8722 | 0.8751 | 0.8753 | 0.8722 | 0.8751 | 0.8751 |
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| 0.0539 | 2.88 | 3400 | 0.7020 | 0.8728 | 0.8745 | 0.8713 | 0.8745 | 0.8751 | 0.8713 | 0.8745 | 0.8745 |
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### Framework versions
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 1115313586
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version https://git-lfs.github.com/spec/v1
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size 1115313586
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