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| Copyright 2021 The HuggingFace Team. All rights reserved. | |
| Licensed under the Apache License, Version 2.0 (the "License"); | |
| you may not use this file except in compliance with the License. | |
| You may obtain a copy of the License at | |
| http://www.apache.org/licenses/LICENSE-2.0 | |
| Unless required by applicable law or agreed to in writing, software | |
| distributed under the License is distributed on an "AS IS" BASIS, | |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| See the License for the specific language governing permissions and | |
| limitations under the License. | |
| --> | |
| # Summarization example | |
| This script shows an example of training a *summarization* model with the 🤗 Transformers library. | |
| For straightforward use-cases you may be able to use these scripts without modification, although we have also | |
| included comments in the code to indicate areas that you may need to adapt to your own projects. | |
| ### Multi-GPU and TPU usage | |
| By default, these scripts use a `MirroredStrategy` and will use multiple GPUs effectively if they are available. TPUs | |
| can also be used by passing the name of the TPU resource with the `--tpu` argument. | |
| ### Example command | |
| ``` | |
| python run_summarization.py \ | |
| --model_name_or_path facebook/bart-base \ | |
| --dataset_name cnn_dailymail \ | |
| --dataset_config "3.0.0" \ | |
| --output_dir /tmp/tst-summarization \ | |
| --per_device_train_batch_size 8 \ | |
| --per_device_eval_batch_size 16 \ | |
| --num_train_epochs 3 \ | |
| --do_train \ | |
| --do_eval | |
| ``` |