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--- |
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language: |
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- en |
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base_model: google-t5/t5-base |
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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: 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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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8970588235294118 |
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- name: F1 |
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type: f1 |
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value: 0.926829268292683 |
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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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# MRPC |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5629 |
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- Accuracy: 0.8971 |
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- F1: 0.9268 |
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- Combined Score: 0.9119 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Combined Score | F1 | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:--------------:|:------:|:---------------:| |
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| No log | 1.0 | 115 | 0.7108 | 0.7671 | 0.8234 | 0.5476 | |
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| No log | 2.0 | 230 | 0.8701 | 0.8901 | 0.9100 | 0.3523 | |
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| No log | 3.0 | 345 | 0.8725 | 0.8924 | 0.9122 | 0.3624 | |
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| No log | 4.0 | 460 | 0.8775 | 0.8949 | 0.9123 | 0.3646 | |
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| 0.3744 | 5.0 | 575 | 0.8946 | 0.9099 | 0.9252 | 0.4054 | |
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| 0.3744 | 6.0 | 690 | 0.8897 | 0.9057 | 0.9217 | 0.4624 | |
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| 0.3744 | 7.0 | 805 | 0.5530 | 0.8873 | 0.9212 | 0.9042 | |
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| 0.3744 | 8.0 | 920 | 0.5405 | 0.8897 | 0.9220 | 0.9059 | |
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| 0.0877 | 9.0 | 1035 | 0.5629 | 0.8971 | 0.9268 | 0.9119 | |
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| 0.0877 | 10.0 | 1150 | 0.5856 | 0.8922 | 0.9241 | 0.9081 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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