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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: selectra-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: 0.737 |
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- name: F1 |
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type: f1 |
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value: 0.7437773019932409 |
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- name: Precision |
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type: precision |
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value: 0.7524857881639091 |
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- name: Recall |
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type: recall |
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value: 0.737 |
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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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# selectra-small-finetuned-amazon-review |
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This model is a fine-tuned version of [Recognai/selectra_small](https://huggingface.co/Recognai/selectra_small) on the amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6279 |
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- Accuracy: 0.737 |
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- F1: 0.7438 |
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- Precision: 0.7525 |
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- Recall: 0.737 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 0.5 | 500 | 0.7041 | 0.7178 | 0.6724 | 0.6715 | 0.7178 | |
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| 0.7908 | 1.0 | 1000 | 0.6365 | 0.7356 | 0.7272 | 0.7211 | 0.7356 | |
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| 0.7908 | 1.5 | 1500 | 0.6204 | 0.7376 | 0.7380 | 0.7387 | 0.7376 | |
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| 0.6358 | 2.0 | 2000 | 0.6162 | 0.7386 | 0.7377 | 0.7380 | 0.7386 | |
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| 0.6358 | 2.5 | 2500 | 0.6228 | 0.7274 | 0.7390 | 0.7576 | 0.7274 | |
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| 0.5827 | 3.0 | 3000 | 0.6188 | 0.7378 | 0.7400 | 0.7425 | 0.7378 | |
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| 0.5827 | 3.5 | 3500 | 0.6246 | 0.7374 | 0.7416 | 0.7467 | 0.7374 | |
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| 0.5427 | 4.0 | 4000 | 0.6266 | 0.7446 | 0.7452 | 0.7465 | 0.7446 | |
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| 0.5427 | 4.5 | 4500 | 0.6331 | 0.7392 | 0.7421 | 0.7456 | 0.7392 | |
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| 0.5184 | 5.0 | 5000 | 0.6279 | 0.737 | 0.7438 | 0.7525 | 0.737 | |
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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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