Closed haywoodsloan closed 1 month ago
abhishekkrthakur
commented
1 month ago 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
commented
1 month ago @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
commented
1 month ago 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
commented
1 month ago 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.in the output folder, you must have README.md. could you please copy paste its contents?
haywoodsloan
commented
1 month ago 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: 0.6I've also attached the full log files. May22_17-11-20_c2798dce683b.zip
abhishekkrthakur
commented
1 month ago 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: truewith 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: 0.9833948339483395It seems like you have some version conflict. do you mind installing autotrain in a new environment and try?
haywoodsloan
commented
1 month ago 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 availableI'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) && \
bashWhen 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
commented
1 month ago 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
Prerequisites
Backend
Local
Interface Used
CLI
CLI Command
autotrain --config /var/hf/config/google/vit-large-patch16-224.ymlUI Screenshots & Parameters
Error Logs
Additional Information
The dataset name used in the new model's README.md is just the
data_path, so a local directory will cause an invalid dataset name error when uploading the model.For example, the model card's dataset name for image classification training is set here: https://github.com/huggingface/autotrain-advanced/blob/9c2c7b56eb2704ac16f4923d723b89b7c5364238/src/autotrain/trainers/image_classification/utils.py#L133-L136
It would be nice if this value was omitted for local data paths. An even better solution could be to add an additional config param to specify the Hugging Face dataset name in addition to the data path. This would enable scenarios where the dataset is checked out locally, but the model will still link to the correct dataset when published.
Thank you!