Hungarian word vectors for HuSpaCy. 

The model is trained on the Hungarian Webcorpus 2.0 using floret with the following hyperparameters: `floret cbow -dim 300 -mode floret -bucket 200000 -minn 4 -maxn 6 -minCount 100 -neg 10 -hashCount 2 -lr 0.01 -thread 70 -epoch 40`

Vectors are published in fasttext and floret format.

| Feature | Description |
| --- | --- |
| **Name** | `hu_vectors_web_lg` |
| **Version** | `1.0` |
| **Vectors** | 200000 keys (300 dimensions) |
| **Sources** | [Hungarian Webcorpus 2.0](https://hlt.bme.hu/en/resources/webcorpus2) (Dávid Márk Nemeskey (SZTAKI-HLT)) |
| **License** | `cc-by-sa-4.0` |
| **Author** | [SzegedAI, MILAB](https://github.com/huspacy/huspacy) |


### Accuracy

| Type | Score |
| --- | --- |
| `ACC` | 10.94 |
| `MRR` | 0.2107 |
{"language": ["hu"], "license": "cc-by-sa-4.0", "tags": ["spacy", "floret", "fasttext", "feature-extraction", "token-classification"]}
spacy floret fasttext feature-extraction token-classification hu license:cc-by-sa-4.0 model-index region:us
TAGS
#spacy #floret #fasttext #feature-extraction #token-classification #hu #license-cc-by-sa-4.0 #model-index #region-us 

Hungarian word vectors for HuSpaCy.


The model is trained on the Hungarian Webcorpus 2.0 using floret with the following hyperparameters: 'floret cbow -dim 300 -mode floret -bucket 200000 -minn 4 -maxn 6 -minCount 100 -neg 10 -hashCount 2 -lr 0.01 -thread 70 -epoch 40'


Vectors are published in fasttext and floret format.



### Accuracy




### Accuracy
TAGS
#spacy #floret #fasttext #feature-extraction #token-classification #hu #license-cc-by-sa-4.0 #model-index #region-us 
 ### Accuracy
passage: TAGS
#spacy #floret #fasttext #feature-extraction #token-classification #hu #license-cc-by-sa-4.0 #model-index #region-us 
### Accuracy