| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: deberta-v3-large__sst2__train-8-2 |
| | 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-8-2 |
| |
|
| | 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: 0.6794 |
| | - Accuracy: 0.6063 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.6942 | 1.0 | 3 | 0.7940 | 0.25 | |
| | | 0.6068 | 2.0 | 6 | 0.9326 | 0.25 | |
| | | 0.6553 | 3.0 | 9 | 0.7979 | 0.25 | |
| | | 0.475 | 4.0 | 12 | 0.7775 | 0.25 | |
| | | 0.377 | 5.0 | 15 | 0.7477 | 0.25 | |
| | | 0.3176 | 6.0 | 18 | 0.6856 | 0.75 | |
| | | 0.2708 | 7.0 | 21 | 0.6554 | 0.75 | |
| | | 0.2855 | 8.0 | 24 | 0.8129 | 0.5 | |
| | | 0.148 | 9.0 | 27 | 0.7074 | 0.75 | |
| | | 0.0947 | 10.0 | 30 | 0.7090 | 0.75 | |
| | | 0.049 | 11.0 | 33 | 0.7885 | 0.75 | |
| | | 0.0252 | 12.0 | 36 | 0.9203 | 0.75 | |
| | | 0.0165 | 13.0 | 39 | 1.0937 | 0.75 | |
| | | 0.0084 | 14.0 | 42 | 1.2502 | 0.75 | |
| | | 0.0059 | 15.0 | 45 | 1.3726 | 0.75 | |
| | | 0.0037 | 16.0 | 48 | 1.4784 | 0.75 | |
| | | 0.003 | 17.0 | 51 | 1.5615 | 0.75 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.15.0 |
| | - Pytorch 1.10.2+cu102 |
| | - Datasets 1.18.2 |
| | - Tokenizers 0.10.3 |
| |
|
