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README.md
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---
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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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- f1
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model-index:
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- name: jrtec-distilroberta-base-mrpc-glue-omar-espejel
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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: 0.8774509803921569
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- name: F1
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type: f1
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value: 0.9137931034482758
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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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# jrtec-distilroberta-base-mrpc-glue-omar-espejel
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0468
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- Accuracy: 0.8775
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- F1: 0.9138
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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: 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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- num_epochs: 10
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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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| 0.2883 | 1.09 | 500 | 1.0351 | 0.8333 | 0.8790 |
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| 0.3128 | 2.18 | 1000 | 0.7217 | 0.8407 | 0.8812 |
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| 0.1607 | 3.27 | 1500 | 0.9991 | 0.8480 | 0.8946 |
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| 0.1 | 4.36 | 2000 | 1.0454 | 0.8456 | 0.8869 |
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| 0.051 | 5.45 | 2500 | 1.0003 | 0.8824 | 0.9184 |
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| 0.037 | 6.54 | 3000 | 1.1195 | 0.8456 | 0.8948 |
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| 0.028 | 7.63 | 3500 | 1.0448 | 0.8725 | 0.9091 |
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| 0.0189 | 8.71 | 4000 | 1.0478 | 0.8725 | 0.9107 |
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| 0.0099 | 9.8 | 4500 | 1.0468 | 0.8775 | 0.9138 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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