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---
license: apache-2.0
tags:
- generated_from_trainer
- summarization
datasets:
- xsum
- autoevaluate/xsum-sample
metrics:
- rouge
duplicated_from: autoevaluate/summarization
model-index:
- name: autoevaluate/summarization-not-evaluated
results:
- task:
type: summarization
name: Summarization
dataset:
name: autoevaluate/xsum-sample
type: autoevaluate/xsum-sample
config: autoevaluate--xsum-sample
split: test
metrics:
- type: rouge
value: 18.3582
name: ROUGE-1
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTU5NWM4NDBkNzExNGFjYTczMDQzMDJhZTRjOGVkY2Q2N2ZjZDAxNWU4YzVjMmNiZGFlM2JiM2YzMjdhM2EyNSIsInZlcnNpb24iOjF9.3TQeweFaWRhylW8P84o1BeZnXMeZurVRmJjqAW3P-JX-RqiBVVMlxohlo1hvmew6VyZpNvk-4oJYGav1bp-nBw
- type: rouge
value: 3.0753
name: ROUGE-2
verified: true
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- type: rouge
value: 14.8475
name: ROUGE-L
verified: true
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- type: rouge
value: 14.8505
name: ROUGE-LSUM
verified: true
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- type: loss
value: 3.009582281112671
name: loss
verified: true
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- type: gen_len
value: 18.05
name: gen_len
verified: true
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---
<!-- 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. -->
# summarization
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6690
- Rouge1: 23.9405
- Rouge2: 5.0879
- Rougel: 18.4981
- Rougelsum: 18.5032
- Gen Len: 18.7376
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.9249 | 0.08 | 1000 | 2.6690 | 23.9405 | 5.0879 | 18.4981 | 18.5032 | 18.7376 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
|