metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
distilbert-base-uncased-finetuned-emotion
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: 0.1408
- Accuracy: 0.939
- F1: 0.9390
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 |
|---|---|---|---|---|---|
| 0.7839 | 1.0 | 250 | 0.2642 | 0.915 | 0.9155 |
| 0.1986 | 2.0 | 500 | 0.1730 | 0.933 | 0.9328 |
| 0.1352 | 3.0 | 750 | 0.1467 | 0.9395 | 0.9399 |
| 0.1068 | 4.0 | 1000 | 0.1375 | 0.9375 | 0.9376 |
| 0.0899 | 5.0 | 1250 | 0.1408 | 0.939 | 0.9390 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1