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--- |
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language: |
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- en |
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license: apache-2.0 |
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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_add_GLUE_Experiment_mrpc_256 |
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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: 0.7107843137254902 |
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- name: F1 |
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type: f1 |
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value: 0.8233532934131738 |
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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_add_GLUE_Experiment_mrpc_256 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-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: 0.5932 |
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- Accuracy: 0.7108 |
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- F1: 0.8234 |
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- Combined Score: 0.7671 |
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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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- 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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| 0.637 | 1.0 | 15 | 0.6242 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.629 | 2.0 | 30 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6302 | 3.0 | 45 | 0.6248 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.63 | 4.0 | 60 | 0.6241 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6323 | 5.0 | 75 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6299 | 6.0 | 90 | 0.6243 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6325 | 7.0 | 105 | 0.6239 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6301 | 8.0 | 120 | 0.6239 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6324 | 9.0 | 135 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6293 | 10.0 | 150 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6307 | 11.0 | 165 | 0.6239 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6302 | 12.0 | 180 | 0.6240 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6338 | 13.0 | 195 | 0.6237 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6281 | 14.0 | 210 | 0.6225 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6263 | 15.0 | 225 | 0.6183 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6017 | 16.0 | 240 | 0.5932 | 0.7108 | 0.8234 | 0.7671 | |
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| 0.5213 | 17.0 | 255 | 0.6146 | 0.6642 | 0.7540 | 0.7091 | |
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| 0.4383 | 18.0 | 270 | 0.6405 | 0.6912 | 0.7842 | 0.7377 | |
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| 0.3903 | 19.0 | 285 | 0.6910 | 0.6912 | 0.7872 | 0.7392 | |
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| 0.363 | 20.0 | 300 | 0.7221 | 0.6544 | 0.7374 | 0.6959 | |
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| 0.3306 | 21.0 | 315 | 0.7583 | 0.6863 | 0.7808 | 0.7335 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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