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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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+ ---
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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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+ ### Eval results
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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|0.667|0.294|0.381|0.272|
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+ |eval_f1_macro|0.711|0.901|0.868|0.909|
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+ |eval_f1_micro|0.713|0.901|0.868|0.909|
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+ |eval_accuracy_balanced|0.71|0.901|0.867|0.909|
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+ |eval_accuracy|0.713|0.901|0.868|0.909|
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+ |eval_precision_macro|0.711|0.901|0.868|0.909|
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+ |eval_recall_macro|0.71|0.901|0.867|0.909|
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+ |eval_precision_micro|0.713|0.901|0.868|0.909|
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+ |eval_recall_micro|0.713|0.901|0.868|0.909|
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+ |eval_runtime|568.387|4.571|0.829|3.382|
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+ |eval_samples_per_second|14.955|206.945|227.909|223.805|
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+ |eval_steps_per_second|0.118|1.75|2.412|1.774|
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+ |epoch|2.99|2.99|2.99|2.99|
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+ |Size of dataset|8500|946|189|757|
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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