Edit model card

DialogLED-large-5120-QMSum-finetuned

This model is a fine-tuned version of MingZhong/DialogLED-base-16384 on the QMSum dataset.

Model description

More information needed

Intended uses & limitations

Dialogue summarization

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1

Training results

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
1
Safetensors
Model size
162M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for ConvAnalysis/DialogLED-base-16384-QMSum-finetuned

Finetuned
(13)
this model

Dataset used to train ConvAnalysis/DialogLED-base-16384-QMSum-finetuned