mhlucero
January 22, 2022, 11:25pm
1
Hello, This is my first post
I'm using prodigy 1.11.6, spacy 3.1.4, spacy-transformers 1.0.6 and python 3.7.3 for this project.
I begin with some questions about training with spancat
python -m prodigy train dest_path --spancat dataset -m en_core_web_lg --gpu-id 0
Why LOSS TOK2VEC column values are always zero? I'm missing something?
here the model I'm loading is
When I load a model trained using transformers get this error
python -m prodigy train dest_path --spancat dataset -m en_core_web_lg --gpu-id 0
nlp_span =spacy.load(path)
ValueError: Cannot deserialize model: mismatched structure
Please , some help will be most appreciated
Thanks so much, best!
1 Like
Hi @mhlucero , welcome to Prodigy!
For the first question, I'm curious if you're combining models in some way? Is there anything in your pipeline
For the second question, can you try upgrading your spacy-transformers version? Perhaps the error is coming from an incompatible deserealization of an older model. Upgrading to v1.1.x should work!
mhlucero
January 26, 2022, 11:05am
3
mhlucero:
spacy-transformers 1.0.6
Hello Miranda! Thanks so much for your answer!
First Question: Nop, I'm using the standard train spancat, with no modifications on the model or config.
Second, about transformers. I updated the spacy-transformers library and did a retraining, with the same result.
>python -m prodigy train ./spans --spancat spans_adq -m en_core_web_trf --gpu-id 0
ℹ Using GPU: 0
========================= Generating Prodigy config =========================
ℹ Auto-generating config with spaCy
Using 'spacy.ngram_range_suggester.v1' for 'spancat' with sizes 1 to 14 (inferred from data)
ℹ Using config from base model
✔ Generated training config
=========================== Initializing pipeline ===========================
[2022-01-26 01:54:36,369] [INFO] Set up nlp object from config
Components: spancat
Merging training and evaluation data for 1 components
- [spancat] Training: 5604 | Evaluation: 1400 (20% split)
Training: 5247 | Evaluation: 1376
Labels: spancat (4)
[2022-01-26 01:54:37,147] [INFO] Pipeline: ['transformer', 'tagger', 'parser', 'attribute_ruler', 'lemmatizer', 'ner', 'spancat']
[2022-01-26 01:54:37,148] [INFO] Resuming training for: ['transformer']
[2022-01-26 01:54:37,154] [INFO] Created vocabulary
[2022-01-26 01:54:37,155] [INFO] Finished initializing nlp object
[2022-01-26 01:54:38,254] [INFO] Initialized pipeline components: ['spancat']
✔ Initialized pipeline
============================= Training pipeline =============================
Components: spancat
Merging training and evaluation data for 1 components
- [spancat] Training: 5604 | Evaluation: 1400 (20% split)
Training: 5247 | Evaluation: 1376
Labels: spancat (4)
ℹ Pipeline: ['transformer', 'tagger', 'parser', 'attribute_ruler', 'lemmatizer',
'ner', 'spancat']
ℹ Frozen components: ['tagger', 'parser', 'attribute_ruler', 'lemmatizer',
'ner']
ℹ Initial learn rate: 0.0
E # LOSS TRANS... LOSS SPANCAT SPANS_SC_F SPANS_SC_P SPANS_SC_R SCORE
--- ------ ------------- ------------ ---------- ---------- ---------- ------
0 0 0.00 7624.78 1.00 0.50 52.42 0.01
16 1000 0.00 1308630.16 50.70 80.95 36.91 0.51
32 2000 0.00 92991.15 66.33 77.73 57.84 0.66
49 3000 0.00 74833.84 71.21 79.33 64.59 0.71
65 4000 0.00 64684.00 73.33 80.59 67.27 0.73
81 5000 0.00 57694.04 74.62 81.72 68.66 0.75
98 6000 0.00 52803.86 75.42 82.19 69.68 0.75
114 7000 0.00 48827.18 76.11 82.89 70.34 0.76
130 8000 0.00 45509.48 76.48 83.13 70.82 0.76
147 9000 0.00 42590.01 76.94 83.36 71.44 0.77
163 10000 0.00 39692.86 77.30 83.40 72.03 0.77
180 11000 0.00 36962.59 77.37 82.78 72.62 0.77
196 12000 0.00 34527.88 77.95 82.69 73.72 0.78
212 13000 0.00 32684.88 78.36 82.35 74.74 0.78
229 14000 0.00 30843.14 78.41 81.80 75.29 0.78
245 15000 0.00 29531.76 78.61 81.81 75.66 0.79
261 16000 0.00 28393.27 78.80 81.86 75.95 0.79
1 Like
in the forum. Sorry if I make mistakes, so here goes.