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nlptown_bert-base-multilingual-uncased-sentiment

nlptown · View on Hugging Face ↗

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language:

  • en
  • nl
  • de
  • fr
  • it
  • es

license: mit

bert-base-multilingual-uncased-sentiment

Visit the NLP Town website for an updated version of this model, with a 40% error reduction on product reviews.

This is a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish, and Italian. It predicts the sentiment of the review as a number of stars (between 1 and 5).

This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above or for further finetuning on related sentiment analysis tasks.

Training data

Here is the number of product reviews we used for finetuning the model:

Language Number of reviews
English 150k
Dutch 80k
German 137k
French 140k
Italian 72k
Spanish 50k

Accuracy

The fine-tuned model obtained the following accuracy on 5,000 held-out product reviews in each of the languages:

  • Accuracy (exact) is the exact match for the number of stars.
  • Accuracy (off-by-1) is the percentage of reviews where the number of stars the model predicts differs by a maximum of 1 from the number given by the human reviewer.
Language Accuracy (exact) Accuracy (off-by-1)
English 67% 95%
Dutch 57% 93%
German 61% 94%
French 59% 94%
Italian 59% 95%
Spanish 58% 95%

Contact

In addition to this model, NLP Town offers custom models for many languages and NLP tasks.

If you found this model useful, you can buy us a coffee.

Feel free to contact us for questions, feedback and/or requests for similar models.

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Files & hashes

PathSizesha1sha256
README.md2.0 KB (2,040 B)9f2cb07e7437c4a7ebb004ea66530a95857ef291f2719fbf85d3bda03ecd11407429e4b1aa57aace5ddfa1edea668aad50503880
config.json953 B (953 B)0d9fa8cbf31cb620229494f45b3d2f1cf4610560e5387cfa72d4b8f301b7df84365195d25711212b6c3d377cace2b18c3a911a74
model.safetensors638.5 MB (669,464,588 B)fc8ab3aefb2c6204edff8b2d1d9b4c6b9d95d0130435c6c12c80a0a2206137c9fa8f6478fce4f4de88ac3d43d0f0e0da3c8c767b
pytorch_model.bin638.5 MB (669,491,321 B)b9a979ecbf9cd3a2b101e5cba8c225147c7eb0fee72c9084bf53cee1f722b1acc6f7439cce27e9beabddce447653a1af45405183
special_tokens_map.json112 B (112 B)e7b0375001f109a6b8873d756ad4f7bbb15fbaa5303df45a03609e4ead04bc3dc1536d0ab19b5358db685b6f3da123d05ec200e3
tokenizer_config.json39 B (39 B)e3656b2367f556bdf85ad4019a052f5ec170069bbc33e3cc4de965153393572f1a5cd5d2bf18872f8c0a0096ae547beac01cec9c
vocab.txt851.5 KB (871,891 B)03c53303f0ef6535e93372a93be2db71ec46a1e387b44292b452f6c05afa49b2e488e7eedf79ea4f4c39db6f2f4b37764228ef3f

Cite this release

Canonical URL
https://aiseedbank.org/models/nlptown_bert-base-multilingual-uncased-sentiment/
Slug
nlptown_bert-base-multilingual-uncased-sentiment
Infohash
38c6b2afca6519099f5c7b0f3a24a2cabfc6e3e4
License
mit
Signing key fingerprint
85a3b32c3712427b

Every file carries a locally computed sha256 — verify a download against the signed sums: nlptown_bert-base-multilingual-uncased-sentiment.SHA256SUMS (+ minisign signature).

Provenance

Upstream repositorynlptown/bert-base-multilingual-uncased-sentiment
Revision (pinned)8f6f4e3a8f70be4b65d3a4a8762b6d781cda240d
Fetched at2026-09-04T03:19:28Z
License at fetchmit
Snapshot toolhuggingface · seedbank 0.1.0

Trackers

✓ verified · rehash-vs-hf-metadata at 2026-09-04T03:19:43Z

mit1.25 GB (1,339,830,944 bytes)transformerspytorchjaxsafetensorsberttext-classificationendpoints_compatible7 languages (tf, en, nl …)