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--- |
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license: mit |
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base_model: microsoft/deberta-v3-base |
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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-base-zeroshot-v1.1-none |
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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-base-zeroshot-v1.1-none |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1987 |
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- F1 Macro: 0.6760 |
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- F1 Micro: 0.7335 |
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- Accuracy Balanced: 0.7247 |
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- Accuracy: 0.7335 |
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- Precision Macro: 0.6872 |
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- Recall Macro: 0.7247 |
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- Precision Micro: 0.7335 |
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- Recall Micro: 0.7335 |
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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: 32 |
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- eval_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.06 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| |
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| 0.2135 | 1.0 | 30790 | 0.3591 | 0.8469 | 0.8620 | 0.8432 | 0.8620 | 0.8511 | 0.8432 | 0.8620 | 0.8620 | |
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| 0.1573 | 2.0 | 61580 | 0.3712 | 0.8517 | 0.8664 | 0.8478 | 0.8664 | 0.8562 | 0.8478 | 0.8664 | 0.8664 | |
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| 0.1038 | 3.0 | 92370 | 0.4572 | 0.8569 | 0.8701 | 0.8556 | 0.8701 | 0.8583 | 0.8556 | 0.8701 | 0.8701 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.14.6 |
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- Tokenizers 0.12.1 |
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