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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-large
model-index:
- name: deberta-v3-large__sst2__train-8-0
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-8-0
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: 0.7088
- Accuracy: 0.5008
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6705 | 1.0 | 3 | 0.7961 | 0.25 |
| 0.6571 | 2.0 | 6 | 0.8092 | 0.25 |
| 0.7043 | 3.0 | 9 | 0.7977 | 0.25 |
| 0.6207 | 4.0 | 12 | 0.8478 | 0.25 |
| 0.5181 | 5.0 | 15 | 0.9782 | 0.25 |
| 0.4136 | 6.0 | 18 | 1.3151 | 0.25 |
| 0.3702 | 7.0 | 21 | 1.8633 | 0.25 |
| 0.338 | 8.0 | 24 | 2.2119 | 0.25 |
| 0.2812 | 9.0 | 27 | 2.3058 | 0.25 |
| 0.2563 | 10.0 | 30 | 2.3353 | 0.25 |
| 0.2132 | 11.0 | 33 | 2.5921 | 0.25 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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