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[examples/flax] use Repository API for push_to_hub (#13672)

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* use Repository for push_to_hub

* update readme

* update other flax scripts

* update readme

* update qa example

* fix push_to_hub call

* fix typo

* fix more typos

* update readme

* use abosolute path to get repo name

* fix glue script
This commit is contained in:
Suraj Patil
2021-09-30 16:38:07 +05:30
committed by GitHub
parent b90096fe14
commit 7db2a79b38
15 changed files with 183 additions and 292 deletions
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examples/flax/text-classification/README.md
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@@ -21,47 +21,15 @@ limitations under the License.
Based on the script [`run_flax_glue.py`](https://github.com/huggingface/transformers/blob/master/examples/flax/text-classification/run_flax_glue.py).
Fine-tuning the library models for sequence classification on the GLUE benchmark: [General Language Understanding
Evaluation](https://gluebenchmark.com/). This script can fine-tune any of the models on the [hub](https://huggingface.co/models).
To begin with it is recommended to create a model repository to save the trained model and logs.
Here we call the model `"bert-glue-mrpc-test"`, but you can change the model name as you like.
You can do this either directly on [huggingface.co](https://huggingface.co/new) (assuming that
you are logged in) or via the command line:
```
huggingface-cli repo create bert-glue-mrpc-test
```
Next we clone the model repository to add the tokenizer and model files.
```
git clone https://huggingface.co/<your-username>/bert-glue-mrpc-test
```
To ensure that all tensorboard traces will be uploaded correctly, we need to
track them. You can run the following command inside your model repo to do so.
```
cd bert-glue-mrpc-test
git lfs track "*tfevents*"
```
Great, we have set up our model repository. During training, we will automatically
push the training logs and model weights to the repo.
Next, let's add a symbolic link to the `run_flax_glue.py`.
```bash
export TASK_NAME=mrpc
export MODEL_DIR="./bert-glue-mrpc-test"
ln -s ~/transformers/examples/flax/text-classification/run_flax_glue.py run_flax_glue.py
```
Evaluation](https://gluebenchmark.com/). This script can fine-tune any of the models on the [hub](https://huggingface.co/models) and can also be used for a
dataset hosted on our [hub](https://huggingface.co/datasets) or your own data in a csv or a JSON file (the script might need some tweaks in that case,
refer to the comments inside for help).
GLUE is made up of a total of 9 different tasks. Here is how to run the script on one of them:
```bash
export TASK_NAME=mrpc
python run_flax_glue.py \
--model_name_or_path bert-base-cased \
--task_name ${TASK_NAME} \
@@ -69,7 +37,7 @@ python run_flax_glue.py \
--learning_rate 2e-5 \
--num_train_epochs 3 \
--per_device_train_batch_size 4 \
--output_dir ${MODEL_DIR} \
--output_dir ./$TASK_NAME/ \
--push_to_hub
```