metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-tagesschau-subcategories
results: []
distilbert-base-uncased-finetuned-tagesschau-subcategories
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7723
- Accuracy: 0.7267
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| No log | 0.4 | 30 | 1.3433 | 0.5667 |
| No log | 0.8 | 60 | 1.0861 | 0.6933 |
| No log | 1.2 | 90 | 0.9395 | 0.7067 |
| No log | 1.6 | 120 | 0.8647 | 0.68 |
| No log | 2.0 | 150 | 0.8018 | 0.72 |
| No log | 2.4 | 180 | 0.7723 | 0.7267 |
| No log | 2.8 | 210 | 0.7616 | 0.72 |
| No log | 3.2 | 240 | 0.7348 | 0.7067 |
| No log | 3.6 | 270 | 0.7747 | 0.72 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2