metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-multiclass-classification
results: []
distilbert-base-uncased-finetuned-multiclass-classification
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6039
- Accuracy: 0.9045
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: 1.45e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 29
- distributed_type: multi-GPU
- 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 |
|---|---|---|---|---|
| 2.6788 | 1.0 | 2638 | 2.1418 | 0.7233 |
| 1.289 | 2.0 | 5276 | 1.0718 | 0.8385 |
| 0.7581 | 3.0 | 7914 | 0.7530 | 0.8878 |
| 0.5557 | 4.0 | 10552 | 0.6371 | 0.9007 |
| 0.493 | 5.0 | 13190 | 0.6039 | 0.9045 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.13.1+cpu
- Datasets 2.13.1
- Tokenizers 0.19.1