metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_model
results: []
my_awesome_model
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: 0.3837
- Accuracy: 0.8642
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 192 | 0.4443 | 0.8407 |
| No log | 2.0 | 384 | 0.4431 | 0.8407 |
| 0.3652 | 3.0 | 576 | 0.4471 | 0.8407 |
| 0.3652 | 4.0 | 768 | 0.3579 | 0.8642 |
| 0.3652 | 5.0 | 960 | 0.3823 | 0.8642 |
| 0.3287 | 6.0 | 1152 | 0.3654 | 0.8642 |
| 0.3287 | 7.0 | 1344 | 0.3694 | 0.8642 |
| 0.2929 | 8.0 | 1536 | 0.3688 | 0.8642 |
| 0.2929 | 9.0 | 1728 | 0.3817 | 0.8642 |
| 0.2929 | 10.0 | 1920 | 0.3837 | 0.8642 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2