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
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Model tree for StDestiny/DialogLED-base-16384-QMSum-finetuned-10Epochs
Base model
MingZhong/DialogLED-base-16384