---
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
should probably proofread and complete it, then remove this comment. -->

# 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: 1.9256

## 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: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.1986        | 0.1667 | 500  | 2.0156          |
| 2.1414        | 0.3334 | 1000 | 1.9893          |
| 2.1247        | 0.5002 | 1500 | 1.9770          |
| 2.1106        | 0.6669 | 2000 | 1.9640          |
| 2.103         | 0.8336 | 2500 | 1.9548          |
| 2.0974        | 1.0003 | 3000 | 1.9519          |
| 2.0874        | 1.1671 | 3500 | 1.9506          |
| 2.0842        | 1.3338 | 4000 | 1.9470          |
| 2.0799        | 1.5005 | 4500 | 1.9406          |
| 2.0781        | 1.6672 | 5000 | 1.9363          |
| 2.0763        | 1.8339 | 5500 | 1.9371          |
| 2.0664        | 2.0007 | 6000 | 1.9311          |
| 2.0717        | 2.1674 | 6500 | 1.9277          |
| 2.0683        | 2.3341 | 7000 | 1.9247          |
| 2.0622        | 2.5008 | 7500 | 1.9290          |
| 2.0614        | 2.6676 | 8000 | 1.9170          |
| 2.0614        | 2.8343 | 8500 | 1.9239          |
| 2.0646        | 3.0010 | 9000 | 1.9211          |


### Framework versions

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