| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: distilbert-base-uncased-distilled-finetuned-clinc |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # distilbert-base-uncased-distilled-finetuned-clinc |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0979 |
| - Accuracy: 0.9416 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
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|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 48 |
| - eval_batch_size: 48 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 318 | 0.5673 | 0.7035 | |
| | 0.7446 | 2.0 | 636 | 0.2809 | 0.8865 | |
| | 0.7446 | 3.0 | 954 | 0.1765 | 0.9255 | |
| | 0.2754 | 4.0 | 1272 | 0.1369 | 0.9284 | |
| | 0.158 | 5.0 | 1590 | 0.1183 | 0.9361 | |
| | 0.158 | 6.0 | 1908 | 0.1091 | 0.9406 | |
| | 0.1237 | 7.0 | 2226 | 0.1035 | 0.94 | |
| | 0.1088 | 8.0 | 2544 | 0.1008 | 0.94 | |
| | 0.1088 | 9.0 | 2862 | 0.0986 | 0.9416 | |
| | 0.1019 | 10.0 | 3180 | 0.0979 | 0.9416 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.1 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
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|
