---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert-base-uncased
datasets:
- pubmed-summarization
model-index:
- name: distilbert-base-uncased-finetuned-pubmed-lora-trained-tabbas97
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-pubmed-lora-trained-tabbas97

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the pubmed-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9949

## 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
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2258        | 0.8   | 500  | 2.0382          |
| 2.1769        | 1.6   | 1000 | 1.9865          |
| 2.1476        | 2.4   | 1500 | 2.0094          |
| 2.146         | 3.2   | 2000 | 2.0005          |
| 2.1429        | 4.0   | 2500 | 1.9993          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1