|
--- |
|
language: |
|
- ru |
|
- ru-RU |
|
tags: |
|
- t5 |
|
inference: |
|
parameters: |
|
no_repeat_ngram_size: 4 |
|
datasets: |
|
- samsum |
|
widget: |
|
- text: | |
|
Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker? |
|
Philipp: Sure you can use the new Hugging Face Deep Learning Container. |
|
Jeff: ok. |
|
Jeff: and how can I get started? |
|
Jeff: where can I find documentation? |
|
Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face |
|
model-index: |
|
- name: mbart_ruDialogSum |
|
results: |
|
- task: |
|
name: Abstractive Dialogue Summarization |
|
type: abstractive-text-summarization |
|
dataset: |
|
name: "SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization (translated to Russian)" |
|
type: samsum |
|
metrics: |
|
- name: Validation ROGUE-1 |
|
type: rogue-1 |
|
value: 30 |
|
- name: Validation ROGUE-L |
|
type: rogue-l |
|
value: 30 |
|
- name: Test ROGUE-1 |
|
type: rogue-1 |
|
value: 31 |
|
- name: Test ROGUE-L |
|
type: rogue-l |
|
value: 31 |
|
--- |
|
### 📝 Description |
