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--- |
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language: |
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- en |
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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: baseline-ft-mrpc-IRoberta-b-8bit |
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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: 0.8970588235294118 |
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- name: F1 |
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type: f1 |
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value: 0.9257950530035336 |
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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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# baseline-ft-mrpc-IRoberta-b-8bit |
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This model is a fine-tuned version of [vuiseng9/baseline-ft-mrpc-IRoberta-b-unquantized](https://huggingface.co/vuiseng9/baseline-ft-mrpc-IRoberta-b-unquantized) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3871 |
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- Accuracy: 0.8971 |
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- F1: 0.9258 |
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- Combined Score: 0.9114 |
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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-07 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 12.0 |
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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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| 0.0021 | 1.0 | 230 | 0.4017 | 0.8848 | 0.9147 | 0.8998 | |
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| 0.0026 | 2.0 | 460 | 0.4105 | 0.8873 | 0.9173 | 0.9023 | |
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| 0.0026 | 3.0 | 690 | 0.3707 | 0.8946 | 0.9236 | 0.9091 | |
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| 0.0037 | 4.0 | 920 | 0.3893 | 0.8946 | 0.9228 | 0.9087 | |
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| 1.324 | 5.0 | 1150 | 0.3871 | 0.8897 | 0.9204 | 0.9050 | |
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| 0.0227 | 6.0 | 1380 | 0.3951 | 0.8897 | 0.9201 | 0.9049 | |
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| 0.0081 | 7.0 | 1610 | 0.3818 | 0.8824 | 0.9155 | 0.8989 | |
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| 0.0054 | 8.0 | 1840 | 0.3902 | 0.8873 | 0.9181 | 0.9027 | |
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| 0.0383 | 9.0 | 2070 | 0.3659 | 0.8922 | 0.9225 | 0.9073 | |
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| 0.3861 | 10.0 | 2300 | 0.4260 | 0.8652 | 0.9030 | 0.8841 | |
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| 0.0028 | 11.0 | 2530 | 0.3619 | 0.8946 | 0.9234 | 0.9090 | |
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| 0.0957 | 12.0 | 2760 | 0.3871 | 0.8971 | 0.9258 | 0.9114 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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