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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: add_BERT_no_pretrain_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: 0.6838235294117647 |
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- name: F1 |
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type: f1 |
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value: 0.8122270742358079 |
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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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# add_BERT_no_pretrain_mrpc |
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This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6240 |
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- Accuracy: 0.6838 |
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- F1: 0.8122 |
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- Combined Score: 0.7480 |
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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: 0.0005 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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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- mixed_precision_training: Native AMP |
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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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| 1.154 | 1.0 | 29 | 0.6856 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6781 | 2.0 | 58 | 0.6609 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6458 | 3.0 | 87 | 0.6348 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6395 | 4.0 | 116 | 19.6354 | 0.3186 | 0.0071 | 0.1629 | |
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| 1.1486 | 5.0 | 145 | 0.6657 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6446 | 6.0 | 174 | 0.6277 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.644 | 7.0 | 203 | 0.6242 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6337 | 8.0 | 232 | 0.6242 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6388 | 9.0 | 261 | 0.6253 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.634 | 10.0 | 290 | 0.6242 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6346 | 11.0 | 319 | 0.6264 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6338 | 12.0 | 348 | 0.6273 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6343 | 13.0 | 377 | 0.6262 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6339 | 14.0 | 406 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.635 | 15.0 | 435 | 0.6244 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6331 | 16.0 | 464 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6328 | 17.0 | 493 | 0.6267 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6338 | 18.0 | 522 | 0.6257 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6321 | 19.0 | 551 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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