metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: emotions-classifier
results: []
emotions-classifier
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: 0.1407
- 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 |
|---|---|---|---|---|---|
| 0.7953 | 1.0 | 250 | 0.2685 | 0.916 | 0.9160 |
| 0.2028 | 2.0 | 500 | 0.1737 | 0.9315 | 0.9314 |
| 0.1359 | 3.0 | 750 | 0.1537 | 0.936 | 0.9366 |
| 0.1078 | 4.0 | 1000 | 0.1415 | 0.938 | 0.9380 |
| 0.0887 | 5.0 | 1250 | 0.1407 | 0.939 | 0.9390 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1