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mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.1

Zero-Shot Classification
PyTorch
Chinese
deberta-v2
Generated from Trainer
Model card Files Community
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- ---
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- base_model: asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0
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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-v1.1
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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-zeroshot-v1.1
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-
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- This model is a fine-tuned version of [asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0](https://huggingface.co/asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.5335
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- - F1 Macro: 0.8675
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- - F1 Micro: 0.8692
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- - Accuracy Balanced: 0.8674
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- - Accuracy: 0.8692
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- - Precision Macro: 0.8677
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- - Recall Macro: 0.8674
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- - Precision Micro: 0.8692
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- - Recall Micro: 0.8692
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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: 42
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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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- | 0.1975 | 0.17 | 200 | 0.3474 | 0.8688 | 0.8708 | 0.8678 | 0.8708 | 0.8701 | 0.8678 | 0.8708 | 0.8708 |
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- | 0.1974 | 0.34 | 400 | 0.3580 | 0.8600 | 0.8624 | 0.8585 | 0.8624 | 0.8621 | 0.8585 | 0.8624 | 0.8624 |
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- | 0.2054 | 0.51 | 600 | 0.3616 | 0.8520 | 0.8565 | 0.8476 | 0.8565 | 0.8638 | 0.8476 | 0.8565 | 0.8565 |
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- | 0.2094 | 0.68 | 800 | 0.3772 | 0.8658 | 0.8687 | 0.8630 | 0.8687 | 0.8710 | 0.8630 | 0.8687 | 0.8687 |
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- | 0.2118 | 0.85 | 1000 | 0.3701 | 0.8729 | 0.8740 | 0.8747 | 0.8740 | 0.8719 | 0.8747 | 0.8740 | 0.8740 |
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- | 0.1948 | 1.02 | 1200 | 0.3778 | 0.8698 | 0.8714 | 0.8702 | 0.8714 | 0.8696 | 0.8702 | 0.8714 | 0.8714 |
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- | 0.1447 | 1.19 | 1400 | 0.3964 | 0.8666 | 0.8692 | 0.8642 | 0.8692 | 0.8706 | 0.8642 | 0.8692 | 0.8692 |
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- | 0.1723 | 1.35 | 1600 | 0.3855 | 0.8718 | 0.8735 | 0.8716 | 0.8735 | 0.8720 | 0.8716 | 0.8735 | 0.8735 |
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- | 0.1476 | 1.52 | 1800 | 0.4164 | 0.8637 | 0.8661 | 0.8620 | 0.8661 | 0.8661 | 0.8620 | 0.8661 | 0.8661 |
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- | 0.1515 | 1.69 | 2000 | 0.3958 | 0.8724 | 0.8740 | 0.8725 | 0.8740 | 0.8724 | 0.8725 | 0.8740 | 0.8740 |
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- | 0.1378 | 1.86 | 2200 | 0.4390 | 0.8694 | 0.8708 | 0.8699 | 0.8708 | 0.8689 | 0.8699 | 0.8708 | 0.8708 |
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- | 0.1332 | 2.03 | 2400 | 0.4535 | 0.8732 | 0.8745 | 0.8740 | 0.8745 | 0.8726 | 0.8740 | 0.8745 | 0.8745 |
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- | 0.0913 | 2.2 | 2600 | 0.5235 | 0.8638 | 0.8661 | 0.8625 | 0.8661 | 0.8656 | 0.8625 | 0.8661 | 0.8661 |
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- | 0.1076 | 2.37 | 2800 | 0.5339 | 0.8638 | 0.8661 | 0.8623 | 0.8661 | 0.8659 | 0.8623 | 0.8661 | 0.8661 |
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- | 0.09 | 2.54 | 3000 | 0.5388 | 0.8670 | 0.8687 | 0.8667 | 0.8687 | 0.8672 | 0.8667 | 0.8687 | 0.8687 |
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- | 0.0928 | 2.71 | 3200 | 0.5266 | 0.8649 | 0.8666 | 0.8648 | 0.8666 | 0.8650 | 0.8648 | 0.8666 | 0.8666 |
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- | 0.0805 | 2.88 | 3400 | 0.5433 | 0.8658 | 0.8677 | 0.8654 | 0.8677 | 0.8663 | 0.8654 | 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
 
 
 
 
 
 
1
+ ---
2
+ base_model: asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.1
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.1
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+
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+ This model is a fine-tuned version of [asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0](https://huggingface.co/asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0) on the None dataset.
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+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.5335
20
+ - F1 Macro: 0.8675
21
+ - F1 Micro: 0.8692
22
+ - Accuracy Balanced: 0.8674
23
+ - Accuracy: 0.8692
24
+ - Precision Macro: 0.8677
25
+ - Recall Macro: 0.8674
26
+ - Precision Micro: 0.8692
27
+ - Recall Micro: 0.8692
28
+
29
+ ## Model description
30
+
31
+ More information needed
32
+
33
+ ## Intended uses & limitations
34
+
35
+ More information needed
36
+
37
+ ## Training and evaluation data
38
+
39
+ More information needed
40
+
41
+ ## Training procedure
42
+
43
+ ### Training hyperparameters
44
+
45
+ The following hyperparameters were used during training:
46
+ - learning_rate: 2e-05
47
+ - train_batch_size: 16
48
+ - eval_batch_size: 128
49
+ - seed: 42
50
+ - gradient_accumulation_steps: 2
51
+ - total_train_batch_size: 32
52
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
53
+ - 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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+ | 0.1975 | 0.17 | 200 | 0.3474 | 0.8688 | 0.8708 | 0.8678 | 0.8708 | 0.8701 | 0.8678 | 0.8708 | 0.8708 |
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+ | 0.1974 | 0.34 | 400 | 0.3580 | 0.8600 | 0.8624 | 0.8585 | 0.8624 | 0.8621 | 0.8585 | 0.8624 | 0.8624 |
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+ | 0.2054 | 0.51 | 600 | 0.3616 | 0.8520 | 0.8565 | 0.8476 | 0.8565 | 0.8638 | 0.8476 | 0.8565 | 0.8565 |
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+ | 0.2094 | 0.68 | 800 | 0.3772 | 0.8658 | 0.8687 | 0.8630 | 0.8687 | 0.8710 | 0.8630 | 0.8687 | 0.8687 |
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+ | 0.2118 | 0.85 | 1000 | 0.3701 | 0.8729 | 0.8740 | 0.8747 | 0.8740 | 0.8719 | 0.8747 | 0.8740 | 0.8740 |
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+ | 0.1948 | 1.02 | 1200 | 0.3778 | 0.8698 | 0.8714 | 0.8702 | 0.8714 | 0.8696 | 0.8702 | 0.8714 | 0.8714 |
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+ | 0.1447 | 1.19 | 1400 | 0.3964 | 0.8666 | 0.8692 | 0.8642 | 0.8692 | 0.8706 | 0.8642 | 0.8692 | 0.8692 |
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+ | 0.1723 | 1.35 | 1600 | 0.3855 | 0.8718 | 0.8735 | 0.8716 | 0.8735 | 0.8720 | 0.8716 | 0.8735 | 0.8735 |
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+ | 0.1476 | 1.52 | 1800 | 0.4164 | 0.8637 | 0.8661 | 0.8620 | 0.8661 | 0.8661 | 0.8620 | 0.8661 | 0.8661 |
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+ | 0.1515 | 1.69 | 2000 | 0.3958 | 0.8724 | 0.8740 | 0.8725 | 0.8740 | 0.8724 | 0.8725 | 0.8740 | 0.8740 |
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+ | 0.1378 | 1.86 | 2200 | 0.4390 | 0.8694 | 0.8708 | 0.8699 | 0.8708 | 0.8689 | 0.8699 | 0.8708 | 0.8708 |
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+ | 0.1332 | 2.03 | 2400 | 0.4535 | 0.8732 | 0.8745 | 0.8740 | 0.8745 | 0.8726 | 0.8740 | 0.8745 | 0.8745 |
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+ | 0.0913 | 2.2 | 2600 | 0.5235 | 0.8638 | 0.8661 | 0.8625 | 0.8661 | 0.8656 | 0.8625 | 0.8661 | 0.8661 |
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+ | 0.1076 | 2.37 | 2800 | 0.5339 | 0.8638 | 0.8661 | 0.8623 | 0.8661 | 0.8659 | 0.8623 | 0.8661 | 0.8661 |
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+ | 0.09 | 2.54 | 3000 | 0.5388 | 0.8670 | 0.8687 | 0.8667 | 0.8687 | 0.8672 | 0.8667 | 0.8687 | 0.8687 |
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+ | 0.0928 | 2.71 | 3200 | 0.5266 | 0.8649 | 0.8666 | 0.8648 | 0.8666 | 0.8650 | 0.8648 | 0.8666 | 0.8666 |
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+ | 0.0805 | 2.88 | 3400 | 0.5433 | 0.8658 | 0.8677 | 0.8654 | 0.8677 | 0.8663 | 0.8654 | 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|eval_dataset|
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+ | :---: | :---: | :---: | :---: |
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+ |Accuracy|0.87|0.955|0.869|
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+ |Inference text/sec (RTX4060ti, batch=128)|36.0|256.0|32.0|
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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