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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: fnet-large-finetuned-wnli |
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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: GLUE WNLI |
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type: glue |
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args: wnli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.38028169014084506 |
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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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# fnet-large-finetuned-wnli |
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This model is a fine-tuned version of [google/fnet-large](https://huggingface.co/google/fnet-large) on the GLUE WNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6953 |
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- Accuracy: 0.3803 |
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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: 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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- num_epochs: 5.0 |
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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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| 0.7217 | 1.0 | 159 | 0.6864 | 0.5634 | |
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| 0.7056 | 2.0 | 318 | 0.6869 | 0.5634 | |
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| 0.706 | 3.0 | 477 | 0.6875 | 0.5634 | |
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| 0.7032 | 4.0 | 636 | 0.6931 | 0.5634 | |
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| 0.7025 | 5.0 | 795 | 0.6953 | 0.3803 | |
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### Framework versions |
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- Transformers 4.11.0.dev0 |
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- Pytorch 1.9.0 |
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- Datasets 1.12.1 |
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- Tokenizers 0.10.3 |
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