| | --- |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - emotion |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: HumanEmotions |
| | 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: 0.926 |
| | - name: F1 |
| | type: f1 |
| | value: 0.9259588893157831 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # HumanEmotions |
| |
|
| | 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: 0.2155 |
| | - Accuracy: 0.926 |
| | - F1: 0.9260 |
| |
|
| | ## 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: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 2 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | 0.8448 | 1.0 | 250 | 0.3310 | 0.906 | 0.9033 | |
| | | 0.2576 | 2.0 | 500 | 0.2155 | 0.926 | 0.9260 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
