distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.2287
- Accuracy: 0.918
- F1: 0.9182
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 |
|---|---|---|---|---|---|
| 0.8478 | 1.0 | 250 | 0.3294 | 0.9015 | 0.8980 |
| 0.2616 | 2.0 | 500 | 0.2287 | 0.918 | 0.9182 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
- Downloads last month
- 44
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for lewiswatson/distilbert-base-uncased-finetuned-emotion
Base model
distilbert/distilbert-base-uncasedDataset used to train lewiswatson/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionself-reported0.918
- F1 on emotionself-reported0.918
- Accuracy on emotiontest set verified0.918
- Precision Macro on emotiontest set verified0.895
- Precision Micro on emotiontest set verified0.918
- Precision Weighted on emotiontest set verified0.919
- Recall Macro on emotiontest set verified0.860
- Recall Micro on emotiontest set verified0.918
- Recall Weighted on emotiontest set verified0.918
- F1 Macro on emotiontest set verified0.873