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update model card README.md
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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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datasets:
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- amazon_reviews_multi
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metrics:
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- accuracy
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model-index:
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- name: deberta_v3_amazon_reviews
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: amazon_reviews_multi
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type: amazon_reviews_multi
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args: en
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.61
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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_amazon_reviews
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the amazon_reviews_multi dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9723
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- Accuracy: 0.61
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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: 8
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- eval_batch_size: 8
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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_steps: 200
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- num_epochs: 3
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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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| 0.9339 | 0.2 | 5000 | 0.9879 | 0.5876 |
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| 0.9386 | 0.4 | 10000 | 0.9408 | 0.5992 |
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| 0.9127 | 0.6 | 15000 | 0.9118 | 0.6004 |
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| 0.8997 | 0.8 | 20000 | 0.9192 | 0.607 |
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| 0.8853 | 1.0 | 25000 | 0.9167 | 0.6018 |
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| 0.8159 | 1.2 | 30000 | 0.9364 | 0.6064 |
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| 0.8367 | 1.4 | 35000 | 0.9215 | 0.6174 |
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| 0.8322 | 1.6 | 40000 | 0.9076 | 0.6108 |
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| 0.8142 | 1.8 | 45000 | 0.9305 | 0.6148 |
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| 0.8139 | 2.0 | 50000 | 0.9394 | 0.6092 |
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| 0.7279 | 2.2 | 55000 | 0.9868 | 0.605 |
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| 0.715 | 2.4 | 60000 | 0.9865 | 0.6072 |
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| 0.7515 | 2.6 | 65000 | 0.9783 | 0.606 |
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| 0.7363 | 2.8 | 70000 | 0.9765 | 0.6096 |
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| 0.7405 | 3.0 | 75000 | 0.9723 | 0.61 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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