DialogLED-large-5120-QMSum-finetuned-10Epochs
This model is a fine-tuned version of MingZhong/DialogLED-base-16384 on the qmsum dataset.
Model description
More information needed
Intended uses & limitations
For dialouge 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: 10
Training results
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 6
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 StDestiny/DialogLED-base-16384-QMSum-finetuned-10Epochs
Base model
MingZhong/DialogLED-base-16384