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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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- accuracy |
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- f1 |
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model-index: |
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- name: sa_BERT_24_mrpc |
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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 MRPC |
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type: glue |
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config: mrpc |
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split: validation |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7083333333333334 |
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- name: F1 |
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type: f1 |
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value: 0.8199697428139183 |
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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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# sa_BERT_24_mrpc |
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This model is a fine-tuned version of [gokuls/bert_base_24](https://huggingface.co/gokuls/bert_base_24) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6042 |
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- Accuracy: 0.7083 |
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- F1: 0.8200 |
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- Combined Score: 0.7642 |
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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: 4e-05 |
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- train_batch_size: 96 |
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- eval_batch_size: 96 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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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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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.6437 | 1.0 | 39 | 0.6042 | 0.7083 | 0.8200 | 0.7642 | |
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| 0.5784 | 2.0 | 78 | 0.6224 | 0.6544 | 0.7403 | 0.6974 | |
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| 0.4657 | 3.0 | 117 | 0.7196 | 0.6740 | 0.7816 | 0.7278 | |
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| 0.3555 | 4.0 | 156 | 0.8929 | 0.6348 | 0.7418 | 0.6883 | |
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| 0.2516 | 5.0 | 195 | 1.0482 | 0.6078 | 0.6992 | 0.6535 | |
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| 0.1654 | 6.0 | 234 | 1.3865 | 0.5515 | 0.6131 | 0.5823 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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