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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert/distilbert-base-uncased
datasets:
- swag
metrics:
- accuracy
model-index:
- name: fine-tuned-distilbert-base-uncased-swag-peft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# fine-tuned-distilbert-base-uncased-swag-peft
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the swag dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8483
- Accuracy: 0.6567
## 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: 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.012 | 1.0 | 4597 | 0.8999 | 0.6374 |
| 0.9634 | 2.0 | 9194 | 0.8617 | 0.6512 |
| 0.955 | 3.0 | 13791 | 0.8483 | 0.6567 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |