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--- |
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license: apache-2.0 |
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tags: |
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- text-classification |
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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: datasetX |
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type: glue |
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config: mrpc |
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split: train |
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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: 0.8161764705882353 |
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- name: F1 |
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type: f1 |
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value: 0.8747913188647747 |
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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 datasetX dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4901 |
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- Accuracy: 0.8162 |
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- F1: 0.8748 |
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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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| 0.4845 | 1.09 | 500 | 0.4901 | 0.8162 | 0.8748 | |
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| 0.3706 | 2.18 | 1000 | 0.6421 | 0.8162 | 0.8691 | |
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| 0.2003 | 3.27 | 1500 | 0.9711 | 0.8162 | 0.8760 | |
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| 0.1281 | 4.36 | 2000 | 0.8224 | 0.8480 | 0.8893 | |
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| 0.0717 | 5.45 | 2500 | 1.1803 | 0.8113 | 0.8511 | |
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| 0.0344 | 6.54 | 3000 | 1.1759 | 0.8480 | 0.8935 | |
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| 0.0277 | 7.63 | 3500 | 1.2140 | 0.8456 | 0.8927 | |
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| 0.0212 | 8.71 | 4000 | 1.0895 | 0.8554 | 0.8974 | |
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| 0.0071 | 9.8 | 4500 | 1.1849 | 0.8554 | 0.8991 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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