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: 0.2291
- Accuracy: 0.9395
- F1: 0.9395
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1313 | 1.0 | 250 | 0.1574 | 0.9355 | 0.9359 |
| 0.0897 | 2.0 | 500 | 0.1597 | 0.9375 | 0.9368 |
| 0.0818 | 3.0 | 750 | 0.1496 | 0.9395 | 0.9401 |
| 0.068 | 4.0 | 1000 | 0.1707 | 0.9365 | 0.9366 |
| 0.0533 | 5.0 | 1250 | 0.1842 | 0.9365 | 0.9363 |
| 0.043 | 6.0 | 1500 | 0.2020 | 0.9365 | 0.9363 |
| 0.0325 | 7.0 | 1750 | 0.2172 | 0.936 | 0.9359 |
| 0.0279 | 8.0 | 2000 | 0.2262 | 0.9355 | 0.9353 |
| 0.0207 | 9.0 | 2250 | 0.2238 | 0.939 | 0.9392 |
| 0.0188 | 10.0 | 2500 | 0.2291 | 0.9395 | 0.9395 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1