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--- |
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library_name: transformers |
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language: |
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- en |
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license: apache-2.0 |
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base_model: google-bert/bert-base-uncased |
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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: bert-base-uncased_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: 0.7867647058823529 |
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- name: F1 |
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type: f1 |
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value: 0.8481675392670157 |
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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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# bert-base-uncased_mrpc |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4455 |
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- Accuracy: 0.7868 |
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- F1: 0.8482 |
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- Combined Score: 0.8175 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 10 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 0.5933 | 1.0 | 15 | 0.5066 | 0.7745 | 0.8351 | 0.8048 | |
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| 0.4605 | 2.0 | 30 | 0.4455 | 0.7868 | 0.8482 | 0.8175 | |
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| 0.31 | 3.0 | 45 | 0.5169 | 0.8162 | 0.8777 | 0.8469 | |
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| 0.1871 | 4.0 | 60 | 0.4473 | 0.8407 | 0.8862 | 0.8634 | |
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| 0.1453 | 5.0 | 75 | 0.5061 | 0.8235 | 0.8672 | 0.8453 | |
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| 0.0963 | 6.0 | 90 | 0.5724 | 0.8284 | 0.8797 | 0.8541 | |
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| 0.0515 | 7.0 | 105 | 0.7238 | 0.8333 | 0.8863 | 0.8598 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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