metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-finetuning
results: []
distilbert-finetuning
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: 0.8622
- Accuracy: 0.7214
- F1: 0.7360
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.9352 | 1.0 | 53 | 1.9292 | 0.2286 | 0.1424 |
| 1.7661 | 2.0 | 106 | 1.6808 | 0.4 | 0.3464 |
| 1.5131 | 3.0 | 159 | 1.4096 | 0.6357 | 0.6419 |
| 0.9411 | 4.0 | 212 | 1.0246 | 0.6714 | 0.6749 |
| 0.5521 | 5.0 | 265 | 0.8622 | 0.7214 | 0.7360 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1