[Push to Hub fails for local data paths] about autotrain-advanced

[abhishekkrthakur]

unfortunately, i was not able to reproduce it the way you described.
however, ive added a check and it wont push dataset tag when using a local dataset.
please upgrade to 0.7.98+ & let me know if you still face this issue.

[haywoodsloan]

@abhishekkrthakur Unfortunately, this issues is still present in version 0.7.101. I'm still receiving the same error using the same config and CLI command. I think the issue is related to when the data path is a absolute path like /var/hf/images

[abhishekkrthakur]

i tried the same with absolute path too. didnt receive any error. from the code, your problem is visibly resolved. could you please confirm? also, can you provide full logs?

[haywoodsloan]

Yes, I just received the following error when using the previously provided config and CLI command. I confirmed I was using version 0.7.101 with autotrain --version.

train has failed due to an exception: Traceback (most recent call last):
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 304, in hf_raise_for_status
    response.raise_for_status()
  File "/app/env/lib/python3.10/site-packages/requests/models.py", line 1021, in raise_for_status
    raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://huggingface.co/api/validate-yaml

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 3761, in create_commit
    hf_raise_for_status(response)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 358, in hf_raise_for_status
    raise BadRequestError(message, response=response) from e
huggingface_hub.utils._errors.BadRequestError:  (Request ID: Root=1-664a4963-5f30158c220e06ea4643c70e;3e0063dc-b80f-44aa-911a-0836a334f510)

Bad request:
"datasets[0]" with value "/var/hf/images/" is not valid. If possible, use a dataset id from https://hf.co/datasets.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/app/env/lib/python3.10/site-packages/autotrain/trainers/common.py", line 117, in wrapper
    return func(*args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/autotrain/trainers/image_classification/__main__.py", line 208, in train
    api.upload_folder(
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 119, in _inner_fn
    return fn(*args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 1230, in _inner
    return fn(self, *args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 4807, in upload_folder
    commit_info = self.create_commit(
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 119, in _inner_fn
    return fn(*args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 1230, in _inner
    return fn(self, *args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 3765, in create_commit
    raise ValueError(f"Invalid metadata in README.md.\n{message}") from e
ValueError: Invalid metadata in README.md.
- "datasets[0]" with value "/var/hf/images/" is not valid. If possible, use a dataset id from https://hf.co/datasets.

[abhishekkrthakur]

in the output folder, you must have README.md. could you please copy paste its contents?

[haywoodsloan]

Here's the README.md from the model output folder:

---
tags:
- autotrain
- image-classification
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
  example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
  example_title: Teapot
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
  example_title: Palace
datasets:
- /var/hf/images
---

# Model Trained Using AutoTrain

- Problem type: Image Classification

## Validation Metrics
loss: 0.7285889387130737

f1: 0.5

precision: 0.6666666666666666

recall: 0.4

auc: 0.52

accuracy: 0.6

I've also attached the full log files.
May22_17-11-20_c2798dce683b.zip

[abhishekkrthakur]

I just ran this config:

task: image-classification
base_model: google/vit-base-patch16-224
project_name: autotrain-ai-image-detect
log: tensorboard
backend: local

data:
  path: /Users/abhishek/Downloads/Datasets/image_classification/flowers
  train_split: train
  valid_split: null
  column_mapping:
    image_column: image
    target_column: label

params:
  lr: 0.00005
  epochs: 1
  batch_size: 8
  warmup_ratio: 0.1
  gradient_accumulation: 1
  optimizer: adamw_torch
  scheduler: linear
  weight_decay: 0
  max_grad_norm: 1
  seed: 42
  logging_steps: -1
  auto_find_batch_size: false
  mixed_precision: none
  save_total_limit: 1
  evaluation_strategy: epoch
  early_stopping_patience: 5
  early_stopping_threshold: 0.01

hub:
  username: ${HF_USERNAME}
  token: ${HF_TOKEN}
  push_to_hub: true

with the command:

autotrain --config /Users/abhishek/Downloads/Datasets/config.yml

from /Users/abhishek

and it worked successfully and my model was pushed to hub.

The readme contents didnt contain dataset tag:

---
tags:
- autotrain
- image-classification
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
  example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
  example_title: Teapot
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
  example_title: Palace
---

# Model Trained Using AutoTrain

- Problem type: Image Classification

## Validation Metrics
loss: 0.046192716807127

f1_macro: 0.9831967159545663

f1_micro: 0.9833948339483395

f1_weighted: 0.9833459803821667

precision_macro: 0.9842701698279861

precision_micro: 0.9833948339483395

precision_weighted: 0.9835024125781294

recall_macro: 0.9823230808554145

recall_micro: 0.9833948339483395

recall_weighted: 0.9833948339483395

accuracy: 0.9833948339483395

It seems like you have some version conflict. do you mind installing autotrain in a new environment and try?

[haywoodsloan]

I just ran that same config and got this error:

train has failed due to an exception: Traceback (most recent call last):
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 304, in hf_raise_for_status
    response.raise_for_status()
  File "/app/env/lib/python3.10/site-packages/requests/models.py", line 1021, in raise_for_status
    raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://huggingface.co/api/validate-yaml

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 3668, in create_commit
    hf_raise_for_status(response)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 358, in hf_raise_for_status
    raise BadRequestError(message, response=response) from e
huggingface_hub.utils._errors.BadRequestError:  (Request ID: Root=1-664e3758-2faaa1f35dcca87b0c0b2c90;11bae101-997f-41e3-95e9-46b4d229763b)

Bad request:
"datasets[0]" with value "/Users/abhishek/Downloads/Datasets/image_classification/flowers" is not valid. If possible, use a dataset id from https://hf.co/datasets.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/app/env/lib/python3.10/site-packages/autotrain/trainers/common.py", line 117, in wrapper
    return func(*args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/autotrain/trainers/image_classification/__main__.py", line 226, in train
    api.upload_folder(
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 1286, in _inner
    return fn(self, *args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 4724, in upload_folder
    commit_info = self.create_commit(
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 1286, in _inner
    return fn(self, *args, **kwargs)
  File "/app/env/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 3672, in create_commit
    raise ValueError(f"Invalid metadata in README.md.\n{message}") from e
ValueError: Invalid metadata in README.md.
- "datasets[0]" with value "/Users/abhishek/Downloads/Datasets/image_classification/flowers" is not valid. If possible, use a dataset id from https://hf.co/datasets.

The README.md content for the output model is:

---
tags:
- autotrain
- image-classification
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
  example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
  example_title: Teapot
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
  example_title: Palace
datasets:
- /Users/abhishek/Downloads/Datasets/image_classification/flowers
---

# Model Trained Using AutoTrain

- Problem type: Image Classification

## Validation Metrics
No validation metrics available

I'm running autotrain in a docker container built from this Dockerfile:

FROM huggingface/autotrain-advanced:latest
RUN pip uninstall -y autotrain-advanced
RUN pip install -U autotrain-advanced
CMD export HF_USERNAME=$(cat $HF_USER_FILE) && \
  export HF_TOKEN=$(cat $HF_TOKEN_FILE) && \
  bash

When I run which autotrain I get this: /app/env/bin/autotrain. And the current version is now 0.7.104.

I've deleted and rebuilt the container but get the same error.

[abhishekkrthakur]

thanks. hopefully fixed in 0.7.106+ by adding one more check around dataset tag.
latest image is currently building: https://github.com/huggingface/autotrain-advanced/actions/runs/9196666390/job/25295280759