Comments (4)
Hi. What data set are you using? And, are you using --do_lower_case
?
from fastformers.
Hi. What data set are you using? And, are you using
--do_lower_case
?
yes I was using that.
here is some trace of it
Traceback (most recent call last):
File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 121, in worker
result = (True, func(*args, **kwds))
File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 44, in mapstar
return list(map(*args))
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/transformers/data/processors/squad.py", line 142, in squad_convert_example_to_features
return_token_type_ids=True,
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/transformers/tokenization_utils_base.py", line 1521, in encode_plus
**kwargs,
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/transformers/tokenization_utils.py", line 372, in _encode_plus
verbose=verbose,
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/transformers/tokenization_utils.py", line 578, in _prepare_for_model
stride=stride,
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/transformers/tokenization_utils.py", line 675, in truncate_sequences
assert len(ids) > num_tokens_to_remove
AssertionError
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "run_squad.py", line 827, in
main()
File "run_squad.py", line 765, in main
train_dataset = load_and_cache_examples(args, tokenizer, evaluate=False, output_examples=False)
File "run_squad.py", line 459, in load_and_cache_examples
threads=args.threads,
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/transformers/data/processors/squad.py", line 331, in squad_convert_examples_to_features
disable=not tqdm_enabled,
File "/home/saikiran/fastformers/venv/lib/python3.7/site-packages/tqdm/std.py", line 1171, in iter
for obj in iterable:
File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 325, in
return (item for chunk in result for item in chunk)
File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 748, in next
raise value
AssertionError
from fastformers.
We have only implemented SuperGLUE data processing at the moment. MultiRC in SuperGLUE is a QA dataset. You may want to try it. Or, you can follow SuperGLUE data processing implementation for your dataset.
from fastformers.
No activities for 6+ months. Closing.
from fastformers.
Related Issues (18)
- Task-agnostic or task-specific distillation used for CPU inference results? HOT 2
- Which TinyBERT models used for student initialisation? HOT 2
- pruned error HOT 3
- Add possibility to fine-tune on other tasks HOT 1
- SQuAD training issue HOT 1
- Fastformers/Transformers question HOT 4
- fastformer HOT 1
- integrate with Lightning ecosystem CI HOT 2
- AMD CPUs should work just fine HOT 3
- how to convert int8 converted onnx model to tensorrt? HOT 1
- This repo is missing important files
- Support for XLnet HOT 2
- Run the teacher model (BERT-base) baseline Error HOT 2
- run the distilled student with 8-bit quantization (onnxruntime) HOT 6
- Hyperparameters of SuperGLUE finetuning HOT 1
- Optimize fine-tuned model from HuggingFace HOT 3
- Integrate ZORB as an opt-in optimization HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from fastformers.