Unable to finetune transformer based ner model after initial tuning

[jlustgarten]

Discussed in #13394

^{Originally posted by jlustgarten March 23, 2024}

How to reproduce the behaviour

Create a transformer ner model
Train it on data using the cfg and cli which auto-saves it
Create a new cfg file that points to your existing model
Try triggering the training using the CLI
You will get a missing config.json error

Your Environment

• spaCy version: 3.7.2
• Platform: Linux-5.15.146.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
• Python version: 3.10.13

This still is occurring with the same text:
Config:
[paths]
train = null
dev = null
vectors = null
init_tok2vec = null

[system]
gpu_allocator = "pytorch"
seed = 0

[nlp]
lang = "en"
pipeline = ["transformer","ner"]
batch_size = 128
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
tokenizer = {"@Tokenizers":"spacy.Tokenizer.v1"}
vectors = {"@vectors":"spacy.Vectors.v1"}

[components]

[components.ner]
factory = "ner"
incorrect_spans_key = null
moves = null
scorer = {"https://github.com/scorers":"spacy.ner_scorer.v1"}
update_with_oracle_cut_size = 100

[components.ner.model]
@architectures = "spacy.TransitionBasedParser.v2"
state_type = "ner"
extra_state_tokens = false
hidden_width = 64
maxout_pieces = 2
use_upper = false
nO = null

[components.ner.model.tok2vec]
@architectures = "spacy-transformers.TransformerListener.v1"
grad_factor = 1.0
pooling = {"https://github.com/layers":"reduce_mean.v1"}
upstream = "*"

[components.transformer]
factory = "transformer"
max_batch_items = 4096
set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}

[components.transformer.model]
@architectures = "spacy-transformers.TransformerModel.v3"
name = "/home/user/Coding/PatientHistory/original_pt_hist_ner"
mixed_precision = false

[components.transformer.model.get_spans]
@span_getters = "spacy-transformers.strided_spans.v1"
window = 128
stride = 96

[components.transformer.model.grad_scaler_config]

[components.transformer.model.tokenizer_config]
use_fast = true

[components.transformer.model.transformer_config]

[corpora]

[corpora.dev]
@readers = "spacy.Corpus.v1"
path = ${paths.dev}
max_length = 0
gold_preproc = false
limit = 0
augmenter = null

[corpora.train]
@readers = "spacy.Corpus.v1"
path = ${paths.train}
max_length = 0
gold_preproc = false
limit = 0
augmenter = null

[training]
accumulate_gradient = 4
dev_corpus = "corpora.dev"
train_corpus = "corpora.train"
seed = ${system.seed}
gpu_allocator = ${system.gpu_allocator}
dropout = 0.1
patience = 2000
max_epochs = 0
max_steps = 80000
eval_frequency = 200
frozen_components = []
annotating_components = []
before_to_disk = null
before_update = null

[training.batcher]
@batchers = "spacy.batch_by_padded.v1"
discard_oversize = false
size = 2000
buffer = 256
get_length = null

[training.logger]
@Loggers = "spacy.ConsoleLogger.v1"
progress_bar = false

[training.optimizer]
https://github.com/optimizers = "Adam.v1"
beta1 = 0.9
beta2 = 0.999
L2_is_weight_decay = true
L2 = 0.01
grad_clip = 1.0
use_averages = false
eps = 0.00000001

[training.optimizer.learn_rate]
https://github.com/schedules = "warmup_linear.v1"
warmup_steps = 250
total_steps = 200000
initial_rate = 0.00005

[training.score_weights]
ents_f = 1.0
ents_p = 0.0
ents_r = 0.0
ents_per_type = null

[pretraining]

[initialize]
vectors = ${paths.vectors}
init_tok2vec = ${paths.init_tok2vec}
vocab_data = null
lookups = null
before_init = null
after_init = null

[initialize.components]

[initialize.tokenizer]

Here's the CLI:
python -m spacy train '/home/user/Coding/PatientHistory/refine_pt_hist_ner.cfg' --output '/home/user/Coding/PatientHistory/improved_pt_hist_3_22_2024' --paths.train '/home/user/Coding/PatientHistory/train.spacy' --paths.dev '/home/user/Coding/PatientHistory/test.spacy' --gpu-id 0
Here's the output:
ℹ Saving to output directory:
/home/user/Coding/PatientHistory/improved_pt_hist_3_22_2024
ℹ Using GPU: 0

=========================== Initializing pipeline ===========================
/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/utils/generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.
_torch_pytree._register_pytree_node(
/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/utils/generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.
_torch_pytree._register_pytree_node(
Traceback (most recent call last):
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy/main.py", line 4, in
setup_cli()
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy/cli/_util.py", line 87, in setup_cli
command(prog_name=COMMAND)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/click/core.py", line 1157, in call
return self.main(*args, **kwargs)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/typer/core.py", line 778, in main
return _main(
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/typer/core.py", line 216, in _main
rv = self.invoke(ctx)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/click/core.py", line 783, in invoke
return __callback(*args, **kwargs)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/typer/main.py", line 683, in wrapper
return callback(**use_params) # type: ignore
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy/cli/train.py", line 54, in train_cli
train(config_path, output_path, use_gpu=use_gpu, overrides=overrides)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy/cli/train.py", line 81, in train
nlp = init_nlp(config, use_gpu=use_gpu)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy/training/initialize.py", line 95, in init_nlp
nlp.initialize(lambda: train_corpus(nlp), sgd=optimizer)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy/language.py", line 1349, in initialize
proc.initialize(get_examples, nlp=self, **p_settings)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy_transformers/pipeline_component.py", line 351, in initialize
self.model.initialize(X=docs)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/thinc/model.py", line 318, in initialize
self.init(self, X=X, Y=Y)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy_transformers/layers/transformer_model.py", line 131, in init
hf_model = huggingface_from_pretrained(name, tok_cfg, trf_cfg)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/spacy_transformers/layers/transformer_model.py", line 267, in huggingface_from_pretrained
tokenizer = tokenizer_cls.from_pretrained(str_path, **tok_config)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 752, in from_pretrained
config = AutoConfig.from_pretrained(
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py", line 1082, in from_pretrained
config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/configuration_utils.py", line 644, in get_config_dict
config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/configuration_utils.py", line 699, in _get_config_dict
resolved_config_file = cached_file(
File "/home/user/miniconda3/envs/patienthistoryclassifier/lib/python3.10/site-packages/transformers/utils/hub.py", line 360, in cached_file
raise EnvironmentError(
OSError: /home/user/Coding/PatientHistory/original_pt_hist_ner does not appear to have a file named config.json. Checkout 'https://huggingface.co//home/user/Coding/PatientHistory/original_pt_hist_ner/None' for available files.