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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: flan-t5-xl-deepspeed-zero3-summary
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: test
args: 3.0.0
metrics:
- name: Rouge1
type: rouge
value: 42.6105
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flan-t5-xl-deepspeed-zero3-summary
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4054
- Rouge1: 42.6105
- Rouge2: 20.2181
- Rougel: 29.7866
- Rougelsum: 39.4431
- Gen Len: 98.0013
## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 10
- total_train_batch_size: 80
- total_eval_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.6011 | 1.0 | 3589 | 1.4054 | 42.6105 | 20.2181 | 29.7866 | 39.4431 | 98.0013 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0
- Datasets 2.9.0
- Tokenizers 0.13.3
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