| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | base_model: microsoft/deberta-v3-large |
| | model-index: |
| | - name: deberta-v3-large__sst2__train-16-1 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # deberta-v3-large__sst2__train-16-1 |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6804 |
| | - Accuracy: 0.5497 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 50 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.7086 | 1.0 | 7 | 0.7176 | 0.2857 | |
| | | 0.6897 | 2.0 | 14 | 0.7057 | 0.2857 | |
| | | 0.6491 | 3.0 | 21 | 0.6582 | 0.8571 | |
| | | 0.567 | 4.0 | 28 | 0.4480 | 0.8571 | |
| | | 0.4304 | 5.0 | 35 | 0.5465 | 0.7143 | |
| | | 0.0684 | 6.0 | 42 | 0.5408 | 0.8571 | |
| | | 0.0339 | 7.0 | 49 | 0.6501 | 0.8571 | |
| | | 0.0082 | 8.0 | 56 | 0.9152 | 0.8571 | |
| | | 0.0067 | 9.0 | 63 | 2.5162 | 0.5714 | |
| | | 0.0045 | 10.0 | 70 | 1.1136 | 0.8571 | |
| | | 0.0012 | 11.0 | 77 | 1.1668 | 0.8571 | |
| | | 0.0007 | 12.0 | 84 | 1.2071 | 0.8571 | |
| | | 0.0005 | 13.0 | 91 | 1.2310 | 0.8571 | |
| | | 0.0006 | 14.0 | 98 | 1.2476 | 0.8571 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.15.0 |
| | - Pytorch 1.10.2+cu102 |
| | - Datasets 1.18.2 |
| | - Tokenizers 0.10.3 |
| |
|
