metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion-assignment01
results: []
distilbert-base-uncased-finetuned-emotion-assignment01
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1766
- Accuracy: 0.9365
- F1: 0.9366
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8475 | 1.0 | 250 | 0.2908 | 0.911 | 0.9098 |
| 0.2382 | 2.0 | 500 | 0.1928 | 0.929 | 0.9291 |
| 0.1601 | 3.0 | 750 | 0.1766 | 0.9365 | 0.9366 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1