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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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- glue
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metrics:
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- accuracy
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- f1
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model-index:
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- name: data2vec-text-base-finetuned-mrpc
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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
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type: glue
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args: mrpc
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8627450980392157
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- name: F1
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type: f1
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value: 0.8992805755395683
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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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# data2vec-text-base-finetuned-mrpc
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This model is a fine-tuned version of [facebook/data2vec-text-base](https://huggingface.co/facebook/data2vec-text-base) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4087
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- Accuracy: 0.8627
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- F1: 0.8993
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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: 9.486061628311107e-06
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- train_batch_size: 4
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- eval_batch_size: 16
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- seed: 19
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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: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.6197 | 1.0 | 917 | 0.4720 | 0.8039 | 0.8606 |
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| 0.4763 | 2.0 | 1834 | 0.4087 | 0.8627 | 0.8993 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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