From 415071b4c2c423d15ec72d28ddc7d62a8f6db8c5 Mon Sep 17 00:00:00 2001 From: Suraj Patil Date: Fri, 25 Sep 2020 17:30:36 +0530 Subject: [PATCH] doc changes (#7385) --- examples/README.md | 10 +++++----- examples/seq2seq/README.md | 2 ++ 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/examples/README.md b/examples/README.md index b9e002eb60..deb5b5d51e 100644 --- a/examples/README.md +++ b/examples/README.md @@ -23,11 +23,11 @@ This is still a work-in-progress – in particular documentation is still sparse | [**`multiple-choice`**](https://github.com/huggingface/transformers/tree/master/examples/multiple-choice) | SWAG, RACE, ARC | ✅ | ✅ | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ViktorAlm/notebooks/blob/master/MPC_GPU_Demo_for_TF_and_PT.ipynb) | [**`question-answering`**](https://github.com/huggingface/transformers/tree/master/examples/question-answering) | SQuAD | ✅ | ✅ | - | - | [**`text-generation`**](https://github.com/huggingface/transformers/tree/master/examples/text-generation) | - | n/a | n/a | n/a | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/02_how_to_generate.ipynb) -| [**`distillation`**](https://github.com/huggingface/transformers/tree/master/examples/distillation) | All | - | - | - | - -| [**`summarization`**](https://github.com/huggingface/transformers/tree/master/examples/seq2seq) | CNN/Daily Mail | - | - | ✅ | - -| [**`translation`**](https://github.com/huggingface/transformers/tree/master/examples/seq2seq) | WMT | - | - | ✅ | - -| [**`bertology`**](https://github.com/huggingface/transformers/tree/master/examples/bertology) | - | - | - | - | - -| [**`adversarial`**](https://github.com/huggingface/transformers/tree/master/examples/adversarial) | HANS | ✅ | - | - | - +| [**`distillation`**](https://github.com/huggingface/transformers/tree/master/examples/distillation) | All | - | - | - | - +| [**`summarization`**](https://github.com/huggingface/transformers/tree/master/examples/seq2seq) | CNN/Daily Mail | ✅ | - | ✅ | - +| [**`translation`**](https://github.com/huggingface/transformers/tree/master/examples/seq2seq) | WMT | ✅ | - | ✅ | - +| [**`bertology`**](https://github.com/huggingface/transformers/tree/master/examples/bertology) | - | - | - | - | - +| [**`adversarial`**](https://github.com/huggingface/transformers/tree/master/examples/adversarial) | HANS | ✅ | - | - | -
diff --git a/examples/seq2seq/README.md b/examples/seq2seq/README.md index 93afa25b7b..9eaec29213 100644 --- a/examples/seq2seq/README.md +++ b/examples/seq2seq/README.md @@ -192,6 +192,8 @@ model = AutoModelForSeq2SeqLM.from_pretrained(f'{output_dir}/best_tfmr') ### Fine-tuning using Seq2SeqTrainer To use `Seq2SeqTrainer` for fine-tuning you should use the `finetune_trainer.py` script. It subclasses `Trainer` to extend it for seq2seq training. Except the `Trainer` releated `TrainingArguments`, it shares the same argument names as that of `finetune.py` file. One notable difference is that, calculating generative metrics (BLEU, ROUGE) is optional and is controlled using the `--predict_with_generate` argument, set this argument to calculate BLEU and ROUGE metrics. +With PyTorch 1.6+ it'll automatically use `native AMP` when `--fp16` is set. + To see all the possible command line options, run: ```bash