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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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base_model: Hartunka/bert_base_rand_20_v2 |
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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_rand_20_v2_qqp |
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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 QQP |
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type: glue |
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args: qqp |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.826020281968835 |
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- name: F1 |
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type: f1 |
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value: 0.7738118206958647 |
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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_rand_20_v2_qqp |
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This model is a fine-tuned version of [Hartunka/bert_base_rand_20_v2](https://huggingface.co/Hartunka/bert_base_rand_20_v2) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3937 |
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- Accuracy: 0.8260 |
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- F1: 0.7738 |
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- Combined Score: 0.7999 |
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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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| 0.4751 | 1.0 | 1422 | 0.4373 | 0.7922 | 0.6774 | 0.7348 | |
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| 0.3713 | 2.0 | 2844 | 0.3954 | 0.8183 | 0.7541 | 0.7862 | |
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| 0.2943 | 3.0 | 4266 | 0.3937 | 0.8260 | 0.7738 | 0.7999 | |
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| 0.2317 | 4.0 | 5688 | 0.4349 | 0.8365 | 0.7744 | 0.8055 | |
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| 0.1827 | 5.0 | 7110 | 0.4562 | 0.8395 | 0.7758 | 0.8077 | |
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| 0.1456 | 6.0 | 8532 | 0.5414 | 0.8400 | 0.7782 | 0.8091 | |
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| 0.1186 | 7.0 | 9954 | 0.6398 | 0.8423 | 0.7852 | 0.8137 | |
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| 0.0962 | 8.0 | 11376 | 0.5349 | 0.8401 | 0.7878 | 0.8139 | |
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### Framework versions |
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- Transformers 4.50.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.21.1 |
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