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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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datasets: |
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- asadfgglie/nli-zh-tw-all |
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- asadfgglie/BanBan_2024-10-17-facial_expressions-nli |
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language: |
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- zh |
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pipeline_tag: zero-shot-classification |
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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-nli-2mil7 |
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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: 0.3496 |
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- F1 Macro: 0.8808 |
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- F1 Micro: 0.8813 |
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- Accuracy Balanced: 0.8806 |
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- Accuracy: 0.8813 |
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- Precision Macro: 0.8810 |
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- Recall Macro: 0.8806 |
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- Precision Micro: 0.8813 |
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- Recall Micro: 0.8813 |
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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: 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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### 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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| 0.4669 | 0.17 | 200 | 0.4194 | 0.8011 | 0.8015 | 0.8068 | 0.8015 | 0.8029 | 0.8068 | 0.8015 | 0.8015 | |
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| 0.3921 | 0.34 | 400 | 0.4010 | 0.8139 | 0.8205 | 0.8095 | 0.8205 | 0.8283 | 0.8095 | 0.8205 | 0.8205 | |
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| 0.3468 | 0.51 | 600 | 0.3457 | 0.8459 | 0.8486 | 0.8445 | 0.8486 | 0.8478 | 0.8445 | 0.8486 | 0.8486 | |
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| 0.3299 | 0.68 | 800 | 0.3523 | 0.8595 | 0.8613 | 0.8598 | 0.8613 | 0.8593 | 0.8598 | 0.8613 | 0.8613 | |
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| 0.3192 | 0.85 | 1000 | 0.3372 | 0.8570 | 0.8592 | 0.8563 | 0.8592 | 0.8578 | 0.8563 | 0.8592 | 0.8592 | |
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| 0.3063 | 1.02 | 1200 | 0.3502 | 0.8594 | 0.8602 | 0.8627 | 0.8602 | 0.8585 | 0.8627 | 0.8602 | 0.8602 | |
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| 0.2481 | 1.19 | 1400 | 0.3579 | 0.8600 | 0.8624 | 0.8589 | 0.8624 | 0.8615 | 0.8589 | 0.8624 | 0.8624 | |
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| 0.2447 | 1.35 | 1600 | 0.3617 | 0.8636 | 0.8650 | 0.8649 | 0.8650 | 0.8628 | 0.8649 | 0.8650 | 0.8650 | |
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| 0.2496 | 1.52 | 1800 | 0.3494 | 0.8658 | 0.8677 | 0.8654 | 0.8677 | 0.8661 | 0.8654 | 0.8677 | 0.8677 | |
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| 0.2444 | 1.69 | 2000 | 0.3345 | 0.8644 | 0.8666 | 0.8635 | 0.8666 | 0.8656 | 0.8635 | 0.8666 | 0.8666 | |
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| 0.2217 | 1.86 | 2200 | 0.3452 | 0.8714 | 0.8724 | 0.8737 | 0.8724 | 0.8703 | 0.8737 | 0.8724 | 0.8724 | |
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| 0.2149 | 2.03 | 2400 | 0.3673 | 0.8727 | 0.8740 | 0.8737 | 0.8740 | 0.8719 | 0.8737 | 0.8740 | 0.8740 | |
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| 0.166 | 2.2 | 2600 | 0.3971 | 0.8731 | 0.8751 | 0.8723 | 0.8751 | 0.8741 | 0.8723 | 0.8751 | 0.8751 | |
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| 0.1685 | 2.37 | 2800 | 0.3884 | 0.8696 | 0.8714 | 0.8693 | 0.8714 | 0.8698 | 0.8693 | 0.8714 | 0.8714 | |
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| 0.1737 | 2.54 | 3000 | 0.3896 | 0.8674 | 0.8692 | 0.8672 | 0.8692 | 0.8676 | 0.8672 | 0.8692 | 0.8692 | |
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| 0.1667 | 2.71 | 3200 | 0.3950 | 0.8718 | 0.8735 | 0.8717 | 0.8735 | 0.8718 | 0.8717 | 0.8735 | 0.8735 | |
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| 0.1811 | 2.88 | 3400 | 0.3889 | 0.8707 | 0.8724 | 0.8708 | 0.8724 | 0.8707 | 0.8708 | 0.8724 | 0.8724 | |
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### Eval result |
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|Datasets|asadfgglie/nli-zh-tw-all/test|asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test|eval_dataset|test_dataset| |
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| :---: | :---: | :---: | :---: | :---: | |
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|eval_loss|0.365|0.29|0.389|0.35| |
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|eval_f1_macro|0.875|0.911|0.87|0.881| |
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|eval_f1_micro|0.876|0.911|0.871|0.881| |
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|eval_accuracy_balanced|0.875|0.911|0.87|0.881| |
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|eval_accuracy|0.876|0.911|0.871|0.881| |
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|eval_precision_macro|0.875|0.912|0.87|0.881| |
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|eval_recall_macro|0.875|0.911|0.87|0.881| |
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|eval_precision_micro|0.876|0.911|0.871|0.881| |
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|eval_recall_micro|0.876|0.911|0.871|0.881| |
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|eval_runtime|232.017|4.063|51.192|204.15| |
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|eval_samples_per_second|36.635|232.844|36.9|37.017| |
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|eval_steps_per_second|0.289|1.969|0.293|0.294| |
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|Size of dataset|8500|946|1889|7557| |
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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 |
