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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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- amazon_reviews_multi |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: electra-small-finetuned-amazon-review |
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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: amazon_reviews_multi |
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type: amazon_reviews_multi |
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args: es |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.4948 |
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- name: F1 |
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type: f1 |
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value: 0.49332463542809535 |
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- name: Precision |
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type: precision |
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value: 0.4921725374649701 |
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- name: Recall |
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type: recall |
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value: 0.4948 |
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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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# electra-small-finetuned-amazon-review |
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This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1647 |
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- Accuracy: 0.4948 |
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- F1: 0.4933 |
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- Precision: 0.4922 |
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- Recall: 0.4948 |
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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: 16 |
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- eval_batch_size: 16 |
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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 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.4061 | 1.0 | 1000 | 1.2279 | 0.4496 | 0.4230 | 0.4359 | 0.4496 | |
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| 1.1941 | 2.0 | 2000 | 1.1783 | 0.4782 | 0.4586 | 0.4567 | 0.4782 | |
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| 1.0997 | 3.0 | 3000 | 1.1648 | 0.4966 | 0.4785 | 0.4805 | 0.4966 | |
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| 1.0265 | 4.0 | 4000 | 1.1507 | 0.4996 | 0.4932 | 0.4920 | 0.4996 | |
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| 0.9736 | 5.0 | 5000 | 1.1647 | 0.4948 | 0.4933 | 0.4922 | 0.4948 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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