metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results_classification
results: []
results_classification
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: 0.2517
- Accuracy: 0.9214
- F1: 0.9214
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.152 | 0.0133 | 50 | 0.3216 | 0.9037 | 0.9033 |
| 0.1533 | 0.0267 | 100 | 0.3024 | 0.9096 | 0.9095 |
| 0.1443 | 0.04 | 150 | 0.3356 | 0.9017 | 0.9010 |
| 0.1101 | 0.0533 | 200 | 0.3121 | 0.9134 | 0.9133 |
| 0.1147 | 0.0667 | 250 | 0.3813 | 0.9005 | 0.9002 |
| 0.1611 | 0.08 | 300 | 0.2992 | 0.9134 | 0.9129 |
| 0.1553 | 0.0933 | 350 | 0.2858 | 0.9166 | 0.9166 |
| 0.1268 | 0.1067 | 400 | 0.2769 | 0.9186 | 0.9185 |
| 0.2011 | 0.12 | 450 | 0.2525 | 0.9214 | 0.9215 |
| 0.1845 | 0.1333 | 500 | 0.2517 | 0.9214 | 0.9214 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1