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--- |
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language: en |
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tags: |
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- sagemaker |
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- bert-base-uncased |
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- text classification |
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license: apache-2.0 |
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datasets: |
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- adecorpusv2 |
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model-index: |
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- name: BERT-ade_corpus |
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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: "ade_corpus_v2Ade_corpus_v2_classification" |
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type: ade_corpus |
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metrics: |
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- name: Validation Accuracy |
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type: accuracy |
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value: 92.98 |
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- name: Validation F1 |
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type: f1 |
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value: 82.73 |
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--- |
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## bert-base-uncased |
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This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container. |
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- Problem type: Text Classification(adverse drug effects detection). |
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## Hyperparameters |
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```json |
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{ |
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"do_eval": true, |
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"do_train": true, |
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"fp16": true, |
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"load_best_model_at_end": true, |
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"model_name": "bert-base-uncased", |
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"num_train_epochs": 10, |
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"per_device_eval_batch_size": 16, |
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"per_device_train_batch_size": 16, |
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"learning_rate":5e-5 |
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} |
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``` |
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## Validation Metrics |
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| key | value | |
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| --- | ----- | |
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| eval_accuracy | 0.9298021697511167 | |
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| eval_auc | 0.8902672664394546 | |
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| eval_f1 | 0.827315541601256 | |
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| eval_loss | 0.17835010588169098 | |
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| eval_recall | 0.8234375 | |
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| eval_precision | 0.831230283911672 | |
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""" |
