| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - emotion |
| metrics: |
| - accuracy |
| model-index: |
| - name: bnb-sentiment-model-saagie |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: emotion |
| type: emotion |
| args: split |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9444444444444444 |
| --- |
| |
| <!-- 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. --> |
|
|
| # bnb-sentiment-model-saagie |
|
|
| This model is a fine-tuned version of [j-hartmann/emotion-english-distilroberta-base](https://huggingface.co/j-hartmann/emotion-english-distilroberta-base) on the emotion dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3581 |
| - Accuracy: 0.9444 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.3724 | 1.0 | 1875 | 0.1799 | 0.9367 | |
| | 0.2118 | 2.0 | 3750 | 0.1918 | 0.9456 | |
| | 0.1792 | 3.0 | 5625 | 0.1791 | 0.95 | |
| | 0.1489 | 4.0 | 7500 | 0.1479 | 0.9489 | |
| | 0.1168 | 5.0 | 9375 | 0.2561 | 0.9444 | |
| | 0.081 | 6.0 | 11250 | 0.2863 | 0.9411 | |
| | 0.0521 | 7.0 | 13125 | 0.3168 | 0.9467 | |
| | 0.0345 | 8.0 | 15000 | 0.3581 | 0.9444 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.8.1 |
| - Datasets 2.12.0 |
| - Tokenizers 0.12.1 |
|
|
