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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-16-6
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-16-6
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: 0.6846
- Accuracy: 0.5058
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6673 | 1.0 | 7 | 0.7580 | 0.2857 |
| 0.5896 | 2.0 | 14 | 0.7885 | 0.5714 |
| 0.5294 | 3.0 | 21 | 1.0040 | 0.4286 |
| 0.3163 | 4.0 | 28 | 1.1761 | 0.5714 |
| 0.1315 | 5.0 | 35 | 1.4315 | 0.4286 |
| 0.0312 | 6.0 | 42 | 2.6115 | 0.2857 |
| 0.1774 | 7.0 | 49 | 2.1631 | 0.5714 |
| 0.0052 | 8.0 | 56 | 2.3838 | 0.4286 |
| 0.0043 | 9.0 | 63 | 2.6553 | 0.4286 |
| 0.0032 | 10.0 | 70 | 2.2774 | 0.4286 |
| 0.0015 | 11.0 | 77 | 1.9467 | 0.7143 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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