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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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base_model: microsoft/deberta-v3-large |
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model-index: |
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- name: deberta-v3-large__sst2__train-16-5 |
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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-16-5 |
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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: 0.5433 |
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- Accuracy: 0.7924 |
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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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| 0.6774 | 1.0 | 7 | 0.7450 | 0.2857 | |
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| 0.7017 | 2.0 | 14 | 0.7552 | 0.2857 | |
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| 0.6438 | 3.0 | 21 | 0.7140 | 0.4286 | |
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| 0.3525 | 4.0 | 28 | 0.5570 | 0.7143 | |
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| 0.2061 | 5.0 | 35 | 0.5303 | 0.8571 | |
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| 0.0205 | 6.0 | 42 | 0.6706 | 0.8571 | |
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| 0.0068 | 7.0 | 49 | 0.8284 | 0.8571 | |
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| 0.0029 | 8.0 | 56 | 0.9281 | 0.8571 | |
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| 0.0015 | 9.0 | 63 | 0.9871 | 0.8571 | |
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| 0.0013 | 10.0 | 70 | 1.0208 | 0.8571 | |
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| 0.0008 | 11.0 | 77 | 1.0329 | 0.8571 | |
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| 0.0005 | 12.0 | 84 | 1.0348 | 0.8571 | |
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| 0.0004 | 13.0 | 91 | 1.0437 | 0.8571 | |
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| 0.0005 | 14.0 | 98 | 1.0512 | 0.8571 | |
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| 0.0004 | 15.0 | 105 | 1.0639 | 0.8571 | |
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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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