metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-classifier
results: []
distilbert-base-uncased-classifier
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3165
- Accuracy: 0.8809
- F1: 0.7916
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0 | 0 | 0.6991 | 0.3573 | 0.4668 |
| No log | 0.6006 | 188 | 0.3642 | 0.8505 | 0.7246 |
| No log | 1.2013 | 376 | 0.3155 | 0.8761 | 0.7717 |
| 0.3491 | 1.8019 | 564 | 0.3068 | 0.8833 | 0.7972 |
| 0.3491 | 2.4026 | 752 | 0.3198 | 0.8833 | 0.8016 |
| 0.3491 | 3 | 939 | 0.3165 | 0.8809 | 0.7916 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2