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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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- ecommerce_reviews_with_language_drift |
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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: distilbert_reviews_with_language_drift |
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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: ecommerce_reviews_with_language_drift |
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type: ecommerce_reviews_with_language_drift |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.818 |
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- name: F1 |
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type: f1 |
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value: 0.8167126877417763 |
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widget: |
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- text: "Poor quality of fabric and ridiculously tight at chest. It's way too short." |
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example_title: "Negative" |
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- text: "One worked perfectly, but the other one has a slight leak and we end up with water underneath the filter." |
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example_title: "Neutral" |
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- text: "I liked the price most! Nothing to dislike here!" |
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example_title: "Positive" |
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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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# distilbert_reviews_with_language_drift |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ecommerce_reviews_with_language_drift dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4970 |
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- Accuracy: 0.818 |
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- F1: 0.8167 |
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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: 3 |
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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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| 0.593 | 1.0 | 500 | 0.4723 | 0.799 | 0.7976 | |
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| 0.3714 | 2.0 | 1000 | 0.4679 | 0.818 | 0.8177 | |
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| 0.2652 | 3.0 | 1500 | 0.4970 | 0.818 | 0.8167 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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