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---
tags:
- summarization
- en
- ecnoder-decoder
- xlmroberta
- Abstractive Summarization
- generated_from_trainer
datasets:
- cnn_dailymail
model-index:
- name: xlmroberta-finetune-en-cnn
results:
- task:
type: summarization
name: Summarization
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: test
metrics:
- name: ROUGE-1
type: rouge
value: 0.0
verified: true
- name: ROUGE-2
type: rouge
value: 0.0
verified: true
- name: ROUGE-L
type: rouge
value: 0.0
verified: true
- name: ROUGE-LSUM
type: rouge
value: 0.0
verified: true
- name: loss
type: loss
value: 13.21529483795166
verified: true
- name: gen_len
type: gen_len
value: 20.0
verified: true
---
<!-- 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. -->
# xlmroberta-finetune-en-cnn
This model is a fine-tuned version of [](https://huggingface.co/) on the cnn_dailymail dataset.
## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 5
- label_smoothing_factor: 0.1
### Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.3.0
- Tokenizers 0.12.1
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