| --- |
| language: |
| - en |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| model-index: |
| - name: pixel-base-finetuned-qnli |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: GLUE QNLI |
| type: glue |
| args: qnli |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8859600951857953 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # pixel-base-finetuned-qnli |
|
|
| This model is a fine-tuned version of [Team-PIXEL/pixel-base](https://huggingface.co/Team-PIXEL/pixel-base) on the GLUE QNLI dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9503 |
| - Accuracy: 0.8860 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 3e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 15000 |
| - mixed_precision_training: Apex, opt level O1 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.5451 | 0.31 | 500 | 0.5379 | 0.7282 | |
| | 0.4451 | 0.61 | 1000 | 0.3846 | 0.8318 | |
| | 0.4567 | 0.92 | 1500 | 0.3543 | 0.8525 | |
| | 0.3558 | 1.22 | 2000 | 0.3294 | 0.8638 | |
| | 0.3324 | 1.53 | 2500 | 0.3221 | 0.8666 | |
| | 0.3434 | 1.83 | 3000 | 0.2976 | 0.8774 | |
| | 0.2573 | 2.14 | 3500 | 0.3193 | 0.8750 | |
| | 0.2411 | 2.44 | 4000 | 0.3044 | 0.8794 | |
| | 0.253 | 2.75 | 4500 | 0.2932 | 0.8834 | |
| | 0.1653 | 3.05 | 5000 | 0.3364 | 0.8841 | |
| | 0.1662 | 3.36 | 5500 | 0.3348 | 0.8797 | |
| | 0.1816 | 3.67 | 6000 | 0.3440 | 0.8869 | |
| | 0.1699 | 3.97 | 6500 | 0.3453 | 0.8845 | |
| | 0.1027 | 4.28 | 7000 | 0.4277 | 0.8810 | |
| | 0.0987 | 4.58 | 7500 | 0.4590 | 0.8832 | |
| | 0.0974 | 4.89 | 8000 | 0.4311 | 0.8783 | |
| | 0.0669 | 5.19 | 8500 | 0.5214 | 0.8819 | |
| | 0.0583 | 5.5 | 9000 | 0.5776 | 0.8850 | |
| | 0.065 | 5.8 | 9500 | 0.5646 | 0.8821 | |
| | 0.0381 | 6.11 | 10000 | 0.6252 | 0.8796 | |
| | 0.0314 | 6.41 | 10500 | 0.7222 | 0.8801 | |
| | 0.0453 | 6.72 | 11000 | 0.6951 | 0.8823 | |
| | 0.0264 | 7.03 | 11500 | 0.7620 | 0.8828 | |
| | 0.0215 | 7.33 | 12000 | 0.8160 | 0.8834 | |
| | 0.0176 | 7.64 | 12500 | 0.8583 | 0.8828 | |
| | 0.0245 | 7.94 | 13000 | 0.8484 | 0.8867 | |
| | 0.0124 | 8.25 | 13500 | 0.8927 | 0.8836 | |
| | 0.0112 | 8.55 | 14000 | 0.9368 | 0.8827 | |
| | 0.0154 | 8.86 | 14500 | 0.9405 | 0.8860 | |
| | 0.0046 | 9.16 | 15000 | 0.9503 | 0.8860 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.17.0 |
| - Pytorch 1.11.0+cu113 |
| - Datasets 2.0.0 |
| - Tokenizers 0.11.6 |
| |
