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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- matthews_correlation |
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model-index: |
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- name: paraphrase-MiniLM-L12-v2-CoLA |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE COLA |
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type: glue |
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config: cola |
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split: validation |
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args: cola |
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metrics: |
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- name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.5057060886900621 |
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widget: |
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- text: '"The cat sat on the mat."' |
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example_title: Correct grammatical sentence |
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- text: '"Me and my friend going to the store."' |
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example_title: Incorrect subject-verb agreement |
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- text: '"I ain''t got no money."' |
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example_title: Incorrect verb conjugation and double negative |
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- text: '"She don''t like pizza no more."' |
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example_title: Incorrect verb conjugation and double negative |
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- text: '"They is arriving tomorrow."' |
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example_title: Incorrect verb conjugation |
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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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# paraphrase-MiniLM-L12-v2-CoLA |
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This model is a fine-tuned version of [sentence-transformers/paraphrase-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L12-v2) on the GLUE COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4636 |
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- Matthews Correlation: 0.5057 |
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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: 8e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 16 |
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- seed: 30198 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 16.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------:| |
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| 0.5747 | 1.0 | 67 | 0.5394 | 0.3455 | |
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| 0.5025 | 2.0 | 134 | 0.4999 | 0.4270 | |
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| 0.3698 | 3.0 | 201 | 0.4636 | 0.5057 | |
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| 0.2969 | 4.0 | 268 | 0.5309 | 0.4751 | |
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| 0.2275 | 5.0 | 335 | 0.6238 | 0.4775 | |
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| 0.1859 | 6.0 | 402 | 0.6315 | 0.4867 | |
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| 0.1517 | 7.0 | 469 | 0.7783 | 0.4695 | |
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| 0.1016 | 8.0 | 536 | 0.6762 | 0.4901 | |
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| 0.1017 | 9.0 | 603 | 0.7412 | 0.5046 | |
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| 0.0898 | 10.0 | 670 | 0.7719 | 0.4877 | |
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| 0.0527 | 11.0 | 737 | 0.8627 | 0.4955 | |
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| 0.0582 | 12.0 | 804 | 0.8986 | 0.4738 | |
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| 0.074 | 13.0 | 871 | 0.9469 | 0.4942 | |
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| 0.0508 | 14.0 | 938 | 0.9436 | 0.4918 | |
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| 0.024 | 15.0 | 1005 | 0.9391 | 0.4919 | |
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| 0.0458 | 16.0 | 1072 | 0.9375 | 0.4946 | |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.1 |
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