| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - emotion |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased-finetuned-emotion |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: emotion |
| type: emotion |
| config: split |
| split: validation |
| args: split |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9345 |
| - name: F1 |
| type: f1 |
| value: 0.9344638918723668 |
| --- |
| |
| <!-- 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-finetuned-emotion |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1514 |
| - Accuracy: 0.9345 |
| - F1: 0.9345 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | No log | 1.0 | 125 | 0.4448 | 0.879 | 0.8713 | |
| | 0.6963 | 2.0 | 250 | 0.2099 | 0.922 | 0.9225 | |
| | 0.6963 | 3.0 | 375 | 0.1763 | 0.932 | 0.9324 | |
| | 0.1548 | 4.0 | 500 | 0.1560 | 0.932 | 0.9318 | |
| | 0.1548 | 5.0 | 625 | 0.1514 | 0.9345 | 0.9345 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.14.2 |
| - Tokenizers 0.13.3 |
|
|
