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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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- swag |
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metrics: |
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- accuracy |
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model-index: |
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- name: roberta-base-finetuned-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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# roberta-base-finetuned-swag |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the swag dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4382 |
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- Accuracy: 0.8390 |
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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: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: IPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 40 |
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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: 3 |
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- training precision: Mixed Precision |
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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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| 0.5707 | 1.0 | 574 | 0.4990 | 0.8097 | |
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| 0.5092 | 2.0 | 1148 | 0.4321 | 0.8361 | |
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| 0.3597 | 3.0 | 1722 | 0.4382 | 0.8390 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.10.0+cpu |
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- Datasets 2.7.1 |
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- Tokenizers 0.12.1 |
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