metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emo_une
results: []
distilbert-base-uncased-finetuned-emo_une
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: 0.4619
- Accuracy: 0.79
- F1: 0.7976
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6217 | 1.0 | 26 | 0.5176 | 0.795 | 0.8019 |
| 0.4629 | 2.0 | 52 | 0.4555 | 0.805 | 0.8142 |
| 0.3877 | 3.0 | 78 | 0.4558 | 0.795 | 0.8019 |
| 0.3343 | 4.0 | 104 | 0.4640 | 0.805 | 0.8095 |
| 0.3068 | 5.0 | 130 | 0.4619 | 0.79 | 0.7976 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1