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--- |
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language: |
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- en |
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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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- boolq |
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metrics: |
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- accuracy |
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model_index: |
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- name: distilbert-base-uncased-boolq |
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results: |
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- task: |
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name: Question Answering |
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type: question-answering |
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dataset: |
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name: boolq |
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type: boolq |
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args: default |
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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.7314984709480122 |
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model-index: |
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- name: andi611/distilbert-base-uncased-qa-boolq |
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results: |
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- task: |
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type: natural-language-inference |
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name: Natural Language Inference |
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dataset: |
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name: boolq |
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type: boolq |
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config: default |
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split: validation |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7314984709480122 |
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verified: true |
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- name: Precision |
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type: precision |
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value: 0.766743648960739 |
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verified: true |
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- name: Recall |
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type: recall |
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value: 0.8165272995573045 |
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verified: true |
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- name: AUC |
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type: auc |
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value: 0.7719917242618858 |
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verified: true |
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- name: F1 |
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type: f1 |
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value: 0.7908527870414483 |
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verified: true |
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- name: loss |
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type: loss |
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value: 1.2070027589797974 |
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verified: true |
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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-base-uncased-boolq |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the boolq dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2071 |
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- Accuracy: 0.7315 |
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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: 32 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6506 | 1.0 | 531 | 0.6075 | 0.6681 | |
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| 0.575 | 2.0 | 1062 | 0.5816 | 0.6978 | |
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| 0.4397 | 3.0 | 1593 | 0.6137 | 0.7253 | |
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| 0.2524 | 4.0 | 2124 | 0.8124 | 0.7466 | |
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| 0.126 | 5.0 | 2655 | 1.1437 | 0.7370 | |
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### Framework versions |
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- Transformers 4.8.2 |
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- Pytorch 1.8.1+cu111 |
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- Datasets 1.8.0 |
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- Tokenizers 0.10.3 |
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