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: 0.2205
- Accuracy: 0.9185
- F1: 0.9186
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 |
|---|---|---|---|---|---|
| 0.7975 | 1.0 | 250 | 0.3090 | 0.902 | 0.9014 |
| 0.2422 | 2.0 | 500 | 0.2205 | 0.9185 | 0.9186 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
- 6
Inference API (serverless) is not available, repository is disabled.
Model tree for Rathohan/distilbert-base-uncased-finetuned-emotion
Base model
distilbert/distilbert-base-uncased
Quantized
this model
Dataset used to train Rathohan/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionvalidation set self-reported0.918
- F1 on emotionvalidation set self-reported0.919