metadata
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: large-5-5
results:
- task:
name: Summarization
type: summarization
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 42.4829
large-5-5
This model is a fine-tuned version of x/large-5-5/ on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.5113
- Rouge1: 42.4829
- Rouge2: 19.1818
- Rougel: 34.6161
- Rougelsum: 34.6157
- Gen Len: 25.8424
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.10.0
- Tokenizers 0.13.2