README.md

metadata

license: mit
base_model: october-sd/bart-large-xsum-finetuned-en-sum
tags:
  - summarization
  - generated_from_trainer
model-index:
  - name: bart-large-xsum-finetuned-en-sum-2
    results: []

bart-large-xsum-finetuned-en-sum-2

This model is a fine-tuned version of october-sd/bart-large-xsum-finetuned-en-sum on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.6259

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: 5e-06
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 512
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.99	126	1.6222
No log	1.98	252	1.6259

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.2
• Datasets 2.15.0
• Tokenizers 0.15.2