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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: deberta-v3-large__sst2__train-16-2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# deberta-v3-large__sst2__train-16-2
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6959
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- Accuracy: 0.5008
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 50
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.7079 | 1.0 | 7 | 0.7361 | 0.2857 |
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| 0.6815 | 2.0 | 14 | 0.7659 | 0.2857 |
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| 0.6938 | 3.0 | 21 | 0.7944 | 0.2857 |
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| 0.4584 | 4.0 | 28 | 1.2441 | 0.2857 |
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| 0.4949 | 5.0 | 35 | 1.2285 | 0.5714 |
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| 0.0574 | 6.0 | 42 | 1.7796 | 0.5714 |
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| 0.0156 | 7.0 | 49 | 2.6027 | 0.5714 |
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| 0.0051 | 8.0 | 56 | 2.8717 | 0.5714 |
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| 0.0017 | 9.0 | 63 | 2.8491 | 0.5714 |
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| 0.0023 | 10.0 | 70 | 1.7149 | 0.7143 |
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| 0.001 | 11.0 | 77 | 1.1101 | 0.7143 |
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### Framework versions
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- Transformers 4.15.0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2
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- Tokenizers 0.10.3
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