metadata

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

distilbert-base-uncased-finetuned-pubmed-torch-trained-tabbas97

This model is a fine-tuned version of distilbert-base-uncased on the pubmed-summarization dataset. It achieves the following results on the evaluation set:

Loss: 1.3843

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

Training results

Pre-finetune Perplexity - 11.65
Post-finetune Perplexity - 3.99

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1