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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/distilbert_rand_10_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: distilbert_rand_10_v2_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: 0.6838235294117647 |
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- name: F1 |
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type: f1 |
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value: 0.7867768595041322 |
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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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# distilbert_rand_10_v2_mrpc |
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This model is a fine-tuned version of [Hartunka/distilbert_rand_10_v2](https://huggingface.co/Hartunka/distilbert_rand_10_v2) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5786 |
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- Accuracy: 0.6838 |
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- F1: 0.7868 |
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- Combined Score: 0.7353 |
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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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| 0.6329 | 1.0 | 15 | 0.5952 | 0.6863 | 0.7949 | 0.7406 | |
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| 0.5742 | 2.0 | 30 | 0.5786 | 0.6838 | 0.7868 | 0.7353 | |
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| 0.5006 | 3.0 | 45 | 0.6244 | 0.6838 | 0.7902 | 0.7370 | |
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| 0.3971 | 4.0 | 60 | 0.7714 | 0.7010 | 0.7973 | 0.7492 | |
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| 0.2599 | 5.0 | 75 | 0.9506 | 0.6642 | 0.7523 | 0.7082 | |
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| 0.1453 | 6.0 | 90 | 1.2578 | 0.6397 | 0.7273 | 0.6835 | |
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| 0.0893 | 7.0 | 105 | 1.5317 | 0.6324 | 0.7243 | 0.6783 | |
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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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