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README.md
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Here you can find our NER models:
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|model name | model description | model path | datasets | link to dataset | base model |
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| **Basic** | Basic training on IAHALT | [FusioNER/Basic_IAHALT](https://huggingface.co/FusioNER/Basic_IAHALT) | IAHALT | [FusioNER/Basic](https://huggingface.co/datasets/FusioNER/Basic) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **Vitaly** | Vitaly training on IAHALT (with BI-BI problem[3]) | [FusioNER/Vitaly_NER](https://huggingface.co/FusioNER/Vitaly_NER) | IAHALT | [FusioNER/Vitaly](https://huggingface.co/datasets/FusioNER/Vitaly) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **Name-Sentences** | Training on IAHALT + Name-Sentences[1] | [FusioNER/Name-Sentences](https://huggingface.co/FusioNER/Name-Sentences) | IAHALT | [FusioNER/Name_Sentences](https://huggingface.co/datasets/FusioNER/Name_Sentences) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **Entity-Injection** | Training on IAHALT + Entity-Injection[2] | [FusioNER/Entity-Injection](https://huggingface.co/FusioNER/Entity-Injection) | IAHALT | [FusioNER/Entity_Injection](https://huggingface.co/datasets/FusioNER/Entity_Injection) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **Smart_Injection** | Training on IAHALT + Name-Sentences[1] + Entity-Injection[2] | [FusioNER/Smart_Injection](https://huggingface.co/FusioNER/Smart_Injection) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **NEMO** | Basic training on NEMO dataset| [FusioNER/Nemo](https://huggingface.co/FusioNER/Nemo) | NEMO | [FusioNER/NEMO](https://huggingface.co/datasets/FusioNER/NEMO) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **IAHALT_and_NEMO** | Basic training on IAHALT + NEMO | [FusioNER/IAHALT_and_NEMO](https://huggingface.co/FusioNER/IAHALT_and_NEMO) | IAHALT + NEMO | [FusioNER/IAHALT_and_NEMO](https://huggingface.co/datasets/FusioNER/IAHALT_and_NEMO) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **IAHALT_and_NEMO_PP** | Training on IAHALT + NEMO + Name-Sentences[1] + Entity-Injection[2] | [FusioNER/IAHALT_and_NEMO_and_PP](https://huggingface.co/FusioNER/IAHALT_and_NEMO_and_PP) | IAHALT + NEMO | [FusioNER/IAHALT_and_NEMO_PP](https://huggingface.co/datasets/FusioNER/IAHALT_and_NEMO_PP) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **Animals** | Training on IAHALT + Entity-Injection[2] (of animals names as PER entities) | [FusioNER/Animals](https://huggingface.co/FusioNER/Animals) | IAHALT | [FusioNER/Animals](https://huggingface.co/datasets/FusioNER/Animals) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **PRS-Injection** | Training on IAHALT + Entity-Injection[2] (of PRS names as PER entities) | [FusioNER/PRS-Injection](https://huggingface.co/FusioNER/PRS-Injection) | IAHALT | [FusioNER/PRS_locations](https://huggingface.co/datasets/FusioNER/PRS_locations) | [HeRo](https://huggingface.co/HeNLP/HeRo) |
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| **DICTA_Basic** | Training the [DICTA](https://huggingface.co/dicta-il/dictabert) model on the [basic](https://huggingface.co/datasets/FusioNER/Basic) IAHALT dataset | [FusioNER/Dicta_Small_Basic](https://huggingface.co/FusioNER/Dicta_Small_Basic) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA](https://huggingface.co/dicta-il/dictabert) |
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| **DICTA_Small_Smart** | Training the [DICTA](https://huggingface.co/dicta-il/dictabert) model on IAHALT + Name-Sentences[1] + Entity-Injection[2]] [dataset](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [FusioNER/Dicta_Small_Smart](https://huggingface.co/FusioNER/Dicta_Small_Smart) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA](https://huggingface.co/dicta-il/dictabert) |
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| **DICTA_basic_NER** | Training the [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) model on the [basic](https://huggingface.co/datasets/FusioNER/Basic) IAHALT dataset| [FusioNER/DICTA_basic](https://huggingface.co/FusioNER/DICTA_basic) | IAHALT | [FusioNER/Basic](https://huggingface.co/datasets/FusioNER/Basic) | [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) |
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| **DICTA_smart_NER** | Training the [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) model on IAHALT + Name-Sentences[1] + Entity-Injection[2]] [dataset](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [FusioNER/DICTA_Smart](https://huggingface.co/FusioNER/DICTA_Smart) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) |
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| **DICTA_Large_Smart** | Training the [DICTA Large](https://huggingface.co/dicta-il/dictabert-large) model on IAHALT + Name-Sentences[1] + Entity-Injection[2]] [dataset](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [FusioNER/Dicta_Large_Smart](https://huggingface.co/FusioNER/Dicta_Large_Smart) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA Large](https://huggingface.co/dicta-il/dictabert-large) |
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[1] **Name-Sentences**: Adding to the corpus sentences that contain only the entity we want the network to learn.
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[3] **BI-BI Problem**: Building training corpus when entities from the same type appear in sequence, labeled as continuations of one another.
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For example, the text "讛讗专讬 驻讜讟专 讜专讜谉 讜讜讬讝诇讬" would tagged as **SINGLE** entity. That problem prevent the model to extract entities correctly.
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# Results
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Here you can find our NER models:
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|model name | model description | model path | datasets | link to dataset | base model | entity types |
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|:----------|:------------------|:-----------|:--------:|:----------------|:----------:| :----------- |
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| **Basic** | Basic training on IAHALT | [FusioNER/Basic_IAHALT](https://huggingface.co/FusioNER/Basic_IAHALT) | IAHALT | [FusioNER/Basic](https://huggingface.co/datasets/FusioNER/Basic) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **Vitaly** | Vitaly training on IAHALT (with BI-BI problem[3]) | [FusioNER/Vitaly_NER](https://huggingface.co/FusioNER/Vitaly_NER) | IAHALT | [FusioNER/Vitaly](https://huggingface.co/datasets/FusioNER/Vitaly) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **Name-Sentences** | Training on IAHALT + Name-Sentences[1] | [FusioNER/Name-Sentences](https://huggingface.co/FusioNER/Name-Sentences) | IAHALT | [FusioNER/Name_Sentences](https://huggingface.co/datasets/FusioNER/Name_Sentences) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **Entity-Injection** | Training on IAHALT + Entity-Injection[2] | [FusioNER/Entity-Injection](https://huggingface.co/FusioNER/Entity-Injection) | IAHALT | [FusioNER/Entity_Injection](https://huggingface.co/datasets/FusioNER/Entity_Injection) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **Smart_Injection** | Training on IAHALT + Name-Sentences[1] + Entity-Injection[2] | [FusioNER/Smart_Injection](https://huggingface.co/FusioNER/Smart_Injection) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **NEMO** | Basic training on NEMO dataset| [FusioNER/Nemo](https://huggingface.co/FusioNER/Nemo) | NEMO | [FusioNER/NEMO](https://huggingface.co/datasets/FusioNER/NEMO) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **IAHALT_and_NEMO** | Basic training on IAHALT + NEMO | [FusioNER/IAHALT_and_NEMO](https://huggingface.co/FusioNER/IAHALT_and_NEMO) | IAHALT + NEMO | [FusioNER/IAHALT_and_NEMO](https://huggingface.co/datasets/FusioNER/IAHALT_and_NEMO) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **IAHALT_and_NEMO_PP** | Training on IAHALT + NEMO + Name-Sentences[1] + Entity-Injection[2] | [FusioNER/IAHALT_and_NEMO_and_PP](https://huggingface.co/FusioNER/IAHALT_and_NEMO_and_PP) | IAHALT + NEMO | [FusioNER/IAHALT_and_NEMO_PP](https://huggingface.co/datasets/FusioNER/IAHALT_and_NEMO_PP) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **Animals** | Training on IAHALT + Entity-Injection[2] (of animals names as PER entities) | [FusioNER/Animals](https://huggingface.co/FusioNER/Animals) | IAHALT | [FusioNER/Animals](https://huggingface.co/datasets/FusioNER/Animals) | [HeRo](https://huggingface.co/HeNLP/HeRo) | classic[4] |
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| **PRS-Injection** | Training on IAHALT + Entity-Injection[2] (of PRS names as PER entities) | [FusioNER/PRS-Injection](https://huggingface.co/FusioNER/PRS-Injection) | IAHALT | [FusioNER/PRS_locations](https://huggingface.co/datasets/FusioNER/PRS_locations) | [HeRo](https://huggingface.co/HeNLP/HeRo) |classic[4]
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| **DICTA_Basic** | Training the [DICTA](https://huggingface.co/dicta-il/dictabert) model on the [basic](https://huggingface.co/datasets/FusioNER/Basic) IAHALT dataset | [FusioNER/Dicta_Small_Basic](https://huggingface.co/FusioNER/Dicta_Small_Basic) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA](https://huggingface.co/dicta-il/dictabert) | classic[4]
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| **DICTA_Small_Smart** | Training the [DICTA](https://huggingface.co/dicta-il/dictabert) model on IAHALT + Name-Sentences[1] + Entity-Injection[2]] [dataset](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [FusioNER/Dicta_Small_Smart](https://huggingface.co/FusioNER/Dicta_Small_Smart) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA](https://huggingface.co/dicta-il/dictabert) | classic[4]
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| **DICTA_basic_NER** | Training the [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) model on the [basic](https://huggingface.co/datasets/FusioNER/Basic) IAHALT dataset| [FusioNER/DICTA_basic](https://huggingface.co/FusioNER/DICTA_basic) | IAHALT | [FusioNER/Basic](https://huggingface.co/datasets/FusioNER/Basic) | [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) | classic[4]
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| **DICTA_smart_NER** | Training the [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) model on IAHALT + Name-Sentences[1] + Entity-Injection[2]] [dataset](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [FusioNER/DICTA_Smart](https://huggingface.co/FusioNER/DICTA_Smart) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA-ner](https://huggingface.co/dicta-il/dictabert-ner) | classic[4]
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| **DICTA_Large_Smart** | Training the [DICTA Large](https://huggingface.co/dicta-il/dictabert-large) model on IAHALT + Name-Sentences[1] + Entity-Injection[2]] [dataset](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [FusioNER/Dicta_Large_Smart](https://huggingface.co/FusioNER/Dicta_Large_Smart) | IAHALT | [FusioNER/Smart_Injection](https://huggingface.co/datasets/FusioNER/Smart_Injection) | [DICTA Large](https://huggingface.co/dicta-il/dictabert-large) | classic[4]
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[1] **Name-Sentences**: Adding to the corpus sentences that contain only the entity we want the network to learn.
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[3] **BI-BI Problem**: Building training corpus when entities from the same type appear in sequence, labeled as continuations of one another.
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[4] **Classic**: which types
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For example, the text "讛讗专讬 驻讜讟专 讜专讜谉 讜讜讬讝诇讬" would tagged as **SINGLE** entity. That problem prevent the model to extract entities correctly.
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# Results
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