metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: emotion-analysis-3000
results: []
emotion-analysis-3000
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: 0.0894
- Accuracy: 0.9417
- F1: 0.9392
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0912 | 1.0 | 20841 | 0.0922 | 0.9423 | 0.9436 |
| 0.097 | 2.0 | 41682 | 0.0894 | 0.9417 | 0.9392 |
| 0.0808 | 3.0 | 62523 | 0.0937 | 0.9419 | 0.9393 |
| 0.0852 | 4.0 | 83364 | 0.0989 | 0.9424 | 0.9397 |
Framework versions
- Transformers 4.39.3
- Pytorch 1.13.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2