| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - emotion |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: newsmodelclassification |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: emotion |
| type: emotion |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.927 |
| - name: F1 |
| type: f1 |
| value: 0.9271124951673986 |
| --- |
| |
| <!-- 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. --> |
|
|
| # newsmodelclassification |
|
|
| 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: 0.2065 |
| - Accuracy: 0.927 |
| - F1: 0.9271 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.8011 | 1.0 | 250 | 0.2902 | 0.911 | 0.9090 | |
| | 0.2316 | 2.0 | 500 | 0.2065 | 0.927 | 0.9271 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.20.1 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.3.2 |
| - Tokenizers 0.10.3 |
|
|
