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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-4
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-8-4
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: 1.3023
- Accuracy: 0.7057
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6816 | 1.0 | 3 | 0.8072 | 0.25 |
| 0.6672 | 2.0 | 6 | 0.8740 | 0.25 |
| 0.6667 | 3.0 | 9 | 0.8578 | 0.25 |
| 0.5346 | 4.0 | 12 | 1.0353 | 0.25 |
| 0.4517 | 5.0 | 15 | 1.1030 | 0.25 |
| 0.3095 | 6.0 | 18 | 0.9986 | 0.25 |
| 0.2464 | 7.0 | 21 | 0.9286 | 0.5 |
| 0.1342 | 8.0 | 24 | 0.4063 | 1.0 |
| 0.0851 | 9.0 | 27 | 0.2210 | 1.0 |
| 0.0491 | 10.0 | 30 | 0.2302 | 1.0 |
| 0.0211 | 11.0 | 33 | 0.4020 | 0.75 |
| 0.017 | 12.0 | 36 | 0.2382 | 1.0 |
| 0.0084 | 13.0 | 39 | 0.0852 | 1.0 |
| 0.0051 | 14.0 | 42 | 0.0354 | 1.0 |
| 0.0047 | 15.0 | 45 | 0.0208 | 1.0 |
| 0.0029 | 16.0 | 48 | 0.0155 | 1.0 |
| 0.0022 | 17.0 | 51 | 0.0139 | 1.0 |
| 0.0019 | 18.0 | 54 | 0.0144 | 1.0 |
| 0.0016 | 19.0 | 57 | 0.0168 | 1.0 |
| 0.0013 | 20.0 | 60 | 0.0231 | 1.0 |
| 0.0011 | 21.0 | 63 | 0.0369 | 1.0 |
| 0.0009 | 22.0 | 66 | 0.0528 | 1.0 |
| 0.001 | 23.0 | 69 | 0.0639 | 1.0 |
| 0.0009 | 24.0 | 72 | 0.0670 | 1.0 |
| 0.0009 | 25.0 | 75 | 0.0526 | 1.0 |
| 0.0008 | 26.0 | 78 | 0.0425 | 1.0 |
| 0.0011 | 27.0 | 81 | 0.0135 | 1.0 |
| 0.0007 | 28.0 | 84 | 0.0076 | 1.0 |
| 0.0007 | 29.0 | 87 | 0.0057 | 1.0 |
| 0.0007 | 30.0 | 90 | 0.0049 | 1.0 |
| 0.0008 | 31.0 | 93 | 0.0045 | 1.0 |
| 0.0007 | 32.0 | 96 | 0.0044 | 1.0 |
| 0.0008 | 33.0 | 99 | 0.0043 | 1.0 |
| 0.0005 | 34.0 | 102 | 0.0044 | 1.0 |
| 0.0006 | 35.0 | 105 | 0.0045 | 1.0 |
| 0.0006 | 36.0 | 108 | 0.0046 | 1.0 |
| 0.0007 | 37.0 | 111 | 0.0048 | 1.0 |
| 0.0006 | 38.0 | 114 | 0.0049 | 1.0 |
| 0.0005 | 39.0 | 117 | 0.0050 | 1.0 |
| 0.0005 | 40.0 | 120 | 0.0050 | 1.0 |
| 0.0004 | 41.0 | 123 | 0.0051 | 1.0 |
| 0.0005 | 42.0 | 126 | 0.0051 | 1.0 |
| 0.0004 | 43.0 | 129 | 0.0051 | 1.0 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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