README.md

metadata

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

retnet-summarization_small

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

• Loss: 4.1658

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: 10
• eval_batch_size: 10
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 40
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 10
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.3805	1.0	4610	4.1733
4.3591	2.0	9220	4.1658

Framework versions

• Transformers 4.35.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1