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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- clinc_oos |
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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: bert-base-uncased-finetuned-clinc_oos |
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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: clinc_oos |
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type: clinc_oos |
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config: plus |
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split: test |
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args: plus |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: |
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accuracy: 0.8672727272727273 |
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- name: F1 |
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type: f1 |
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value: |
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f1: 0.8593551627139002 |
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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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# bert-base-uncased-finetuned-clinc_oos |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the clinc_oos dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0863 |
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- Accuracy: {'accuracy': 0.8672727272727273} |
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- F1: {'f1': 0.8593551627139002} |
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## Model Training Details |
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| Parameter | Value | |
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|----------------------|-----------------------------------| |
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| **Task** | text-classification | |
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| **Base Model Name** | bert-base-uncased | |
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| **Dataset Name** | clinc_oos | |
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| **Dataset Config** | plus | |
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| **Batch Size** | 16 | |
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| **Number of Epochs** | 3 | |
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| **Learning Rate** | 0.00002 | |
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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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| 4.3415 | 1.0 | 954 | 2.4724 | {'accuracy': 0.7769090909090909} | {'f1': 0.7596942777117995} | |
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| 1.7949 | 2.0 | 1908 | 1.3415 | {'accuracy': 0.8538181818181818} | {'f1': 0.8441232118060242} | |
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| 0.8898 | 3.0 | 2862 | 1.0863 | {'accuracy': 0.8672727272727273} | {'f1': 0.8593551627139002} | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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