|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: deberta-v3-large__sst2__train-16-8 |
|
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-16-8 |
|
|
|
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: 0.6915 |
|
- Accuracy: 0.6579 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.7129 | 1.0 | 7 | 0.7309 | 0.2857 | |
|
| 0.6549 | 2.0 | 14 | 0.7316 | 0.4286 | |
|
| 0.621 | 3.0 | 21 | 0.7131 | 0.5714 | |
|
| 0.3472 | 4.0 | 28 | 0.5703 | 0.4286 | |
|
| 0.2041 | 5.0 | 35 | 0.6675 | 0.5714 | |
|
| 0.031 | 6.0 | 42 | 1.6750 | 0.5714 | |
|
| 0.0141 | 7.0 | 49 | 1.8743 | 0.5714 | |
|
| 0.0055 | 8.0 | 56 | 1.1778 | 0.5714 | |
|
| 0.0024 | 9.0 | 63 | 1.0699 | 0.5714 | |
|
| 0.0019 | 10.0 | 70 | 1.0933 | 0.5714 | |
|
| 0.0012 | 11.0 | 77 | 1.1218 | 0.7143 | |
|
| 0.0007 | 12.0 | 84 | 1.1468 | 0.7143 | |
|
| 0.0006 | 13.0 | 91 | 1.1584 | 0.7143 | |
|
| 0.0006 | 14.0 | 98 | 1.3092 | 0.7143 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.15.0 |
|
- Pytorch 1.10.2+cu102 |
|
- Datasets 1.18.2 |
|
- Tokenizers 0.10.3 |
|
|