metadata

base_model: kaizerBox/retnet-summarization
tags:
  - generated_from_trainer
datasets:
  - xsum
model-index:
  - name: retnet-summarization
    results: []

retnet-summarization

This model is a fine-tuned version of kaizerBox/retnet-summarization on the xsum dataset. It achieves the following results on the evaluation set:

Loss: 3.5369

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: 0.0006
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.8204	1.0	11525	3.5369

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1