Amrit Puhan
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End of training
Browse files- README.md +66 -0
- model.safetensors +1 -1
README.md
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---
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license: mit
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base_model: MoritzLaurer/deberta-v3-large-zeroshot-v2.0
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tags:
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- generated_from_trainer
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datasets:
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- swag
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metrics:
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- accuracy
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model-index:
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- name: fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-swag
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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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# fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-swag
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This model is a fine-tuned version of [MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0) on the swag dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5968
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- Accuracy: 0.9142
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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: 1.5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 4
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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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| 0.4957 | 1.0 | 4597 | 0.2545 | 0.9058 |
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| 0.2768 | 2.0 | 9194 | 0.2780 | 0.9089 |
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| 0.1333 | 3.0 | 13791 | 0.4016 | 0.9126 |
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| 0.0599 | 4.0 | 18388 | 0.5968 | 0.9142 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 1.11.0
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1740300340
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version https://git-lfs.github.com/spec/v1
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size 1740300340
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