distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the [emotion]( dataset(https://huggingface.co/datasets/emotion) dataset for in the dataset in HG. It achieves the following results on the evaluation set:
- Loss: 0.2033
- Accuracy: 0.9275
- F1: 0.9273
Model description
This model is a copy of the model found in the book Natural Language Processing with Transformers.
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 |
|---|---|---|---|---|---|
| 0.806 | 1.0 | 250 | 0.2954 | 0.908 | 0.9062 |
| 0.2361 | 2.0 | 500 | 0.2033 | 0.9275 | 0.9273 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.12.1+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3
