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README.md

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+---
+language:
+- en
+license: cc-by-sa-4.0
+library_name: span-marker
+tags:
+- span-marker
+- token-classification
+- ner
+- named-entity-recognition
+- generated_from_span_marker_trainer
+datasets:
+- tomaarsen/ner-orgs
+metrics:
+- precision
+- recall
+- f1
+widget:
+- text: The Fellowship of British Baptists and BMS World Mission brings together in
+    ministry the churches that are members of the Baptist Union of Scotland, Wales,
+    the Irish Baptist Networks, and the Baptist Union of Great Britain.
+- text: The program is classified in the National Collegiate Athletic Association
+    (NCAA) Division I Bowl Subdivision (FBS), and the team competes in the Big 12
+    Conference.
+- text: The Human Rights Foundation, condemned the assault, with HRF president Thor
+    Halvorssen Mendoza claiming that "the PSUV approved of the attacks against opposition
+    deputies at the National Assembly ".
+- text: But senior Conservatives, such as Commons Health Committee chairperson Sarah
+    Wollaston and education minister Anne Milton, backed calls for a free vote on
+    the issue, while Labour MP Stella Creasy said she would table an amendment on
+    the matter to the Domestic Violence Bill and said that over 150 parliamentarians
+    had expressed support for the change, and Labour's shadow Attorney General Shami
+    Chakrabarti called the issue a test fo r May's feminism.
+- text: From 1991 to 1992, the Social Democratic Party and Social Democrats of Croatia
+    were a part of the National Union government which was created by Franjo Tuđman
+    during the first stages of the war.
+pipeline_tag: token-classification
+base_model: roberta-large
+model-index:
+- name: SpanMarker with roberta-large on FewNERD, CoNLL2003, and OntoNotes v5
+  results:
+  - task:
+      type: token-classification
+      name: Named Entity Recognition
+    dataset:
+      name: FewNERD, CoNLL2003, and OntoNotes v5
+      type: tomaarsen/ner-orgs
+      split: test
+    metrics:
+    - type: f1
+      value: 0.8050627240143369
+      name: F1
+    - type: precision
+      value: 0.8089771294795606
+      name: Precision
+    - type: recall
+      value: 0.8011860174781523
+      name: Recall
+---
+
+# SpanMarker with roberta-large on FewNERD, CoNLL2003, and OntoNotes v5
+
+This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [FewNERD, CoNLL2003, and OntoNotes v5](https://huggingface.co/datasets/tomaarsen/ner-orgs) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [roberta-large](https://huggingface.co/roberta-large) as the underlying encoder.
+
+## Model Details
+
+### Model Description
+- **Model Type:** SpanMarker
+- **Encoder:** [roberta-large](https://huggingface.co/roberta-large)
+- **Maximum Sequence Length:** 256 tokens
+- **Maximum Entity Length:** 8 words
+- **Training Dataset:** [FewNERD, CoNLL2003, and OntoNotes v5](https://huggingface.co/datasets/tomaarsen/ner-orgs)
+- **Language:** en
+- **License:** cc-by-sa-4.0
+
+### Model Sources
+
+- **Repository:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER)
+- **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf)
+
+### Model Labels
+| Label | Examples                                     |
+|:------|:---------------------------------------------|
+| ORG   | "IAEA", "Church 's Chicken", "Texas Chicken" |
+
+## Evaluation
+
+### Metrics
+| Label   | Precision | Recall | F1     |
+|:--------|:----------|:-------|:-------|
+| **all** | 0.8090    | 0.8012 | 0.8051 |
+| ORG     | 0.8090    | 0.8012 | 0.8051 |
+
+## Uses
+
+### Direct Use for Inference
+
+```python
+from span_marker import SpanMarkerModel
+
+# Download from the 🤗 Hub
+model = SpanMarkerModel.from_pretrained("nbroad/span-marker-roberta-large-orgs-v1")
+# Run inference
+entities = model.predict("The program is classified in the National Collegiate Athletic Association (NCAA) Division I Bowl Subdivision (FBS), and the team competes in the Big 12 Conference.")
+```
+
+### Downstream Use
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+```python
+from span_marker import SpanMarkerModel, Trainer
+
+# Download from the 🤗 Hub
+model = SpanMarkerModel.from_pretrained("nbroad/span-marker-roberta-large-orgs-v1")
+
+# Specify a Dataset with "tokens" and "ner_tag" columns
+dataset = load_dataset("conll2003") # For example CoNLL2003
+
+# Initialize a Trainer using the pretrained model & dataset
+trainer = Trainer(
+    model=model,
+    train_dataset=dataset["train"],
+    eval_dataset=dataset["validation"],
+)
+trainer.train()
+trainer.save_model("nbroad/span-marker-roberta-large-orgs-v1-finetuned")
+```
+</details>
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Set Metrics
+| Training set          | Min | Median  | Max |
+|:----------------------|:----|:--------|:----|
+| Sentence length       | 1   | 23.5706 | 263 |
+| Entities per sentence | 0   | 0.7865  | 39  |
+
+### Training Hyperparameters
+- learning_rate: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training Results
+| Epoch  | Step  | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
+|:------:|:-----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
+| 0.1430 | 600   | 0.0085          | 0.7425               | 0.7383            | 0.7404        | 0.9726              |
+| 0.2860 | 1200  | 0.0078          | 0.7503               | 0.7516            | 0.7510        | 0.9741              |
+| 0.4290 | 1800  | 0.0077          | 0.6962               | 0.8107            | 0.7491        | 0.9718              |
+| 0.5720 | 2400  | 0.0060          | 0.8074               | 0.7486            | 0.7769        | 0.9753              |
+| 0.7150 | 3000  | 0.0057          | 0.8135               | 0.7717            | 0.7921        | 0.9770              |
+| 0.8580 | 3600  | 0.0059          | 0.7997               | 0.7764            | 0.7879        | 0.9763              |
+| 1.0010 | 4200  | 0.0057          | 0.7860               | 0.8051            | 0.7954        | 0.9771              |
+| 1.1439 | 4800  | 0.0058          | 0.7907               | 0.7717            | 0.7811        | 0.9763              |
+| 1.2869 | 5400  | 0.0058          | 0.8116               | 0.7803            | 0.7956        | 0.9774              |
+| 1.4299 | 6000  | 0.0056          | 0.7918               | 0.7850            | 0.7884        | 0.9770              |
+| 1.5729 | 6600  | 0.0056          | 0.8097               | 0.7837            | 0.7965        | 0.9769              |
+| 1.7159 | 7200  | 0.0055          | 0.8113               | 0.7790            | 0.7948        | 0.9765              |
+| 1.8589 | 7800  | 0.0052          | 0.8095               | 0.7970            | 0.8032        | 0.9782              |
+| 2.0019 | 8400  | 0.0054          | 0.8244               | 0.7782            | 0.8006        | 0.9774              |
+| 2.1449 | 9000  | 0.0053          | 0.8238               | 0.7970            | 0.8102        | 0.9782              |
+| 2.2879 | 9600  | 0.0053          | 0.82                 | 0.7901            | 0.8048        | 0.9773              |
+| 2.4309 | 10200 | 0.0053          | 0.8243               | 0.7936            | 0.8086        | 0.9785              |
+| 2.5739 | 10800 | 0.0053          | 0.8159               | 0.7953            | 0.8055        | 0.9781              |
+| 2.7169 | 11400 | 0.0053          | 0.8072               | 0.8034            | 0.8053        | 0.9784              |
+| 2.8599 | 12000 | 0.0052          | 0.8111               | 0.8017            | 0.8064        | 0.9782              |
+
+### Framework Versions
+- Python: 3.10.12
+- SpanMarker: 1.5.0
+- Transformers: 4.35.2
+- PyTorch: 2.1.0a0+32f93b1
+- Datasets: 2.15.0
+- Tokenizers: 0.15.0
+
+## Citation
+
+### BibTeX
+```
+@software{Aarsen_SpanMarker,
+    author = {Aarsen, Tom},
+    license = {Apache-2.0},
+    title = {{SpanMarker for Named Entity Recognition}},
+    url = {https://github.com/tomaarsen/SpanMarkerNER}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

added_tokens.json

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+{
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+  "<start>": 50265
+}

config.json

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+{
+  "architectures": [
+    "SpanMarkerModel"
+  ],
+  "encoder": {
+    "_name_or_path": "roberta-large",
+    "add_cross_attention": false,
+    "architectures": [
+      "RobertaForMaskedLM"
+    ],
+    "attention_probs_dropout_prob": 0.1,
+    "bad_words_ids": null,
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+    "bos_token_id": 0,
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+    "classifier_dropout": null,
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+    "decoder_start_token_id": null,
+    "diversity_penalty": 0.0,
+    "do_sample": false,
+    "early_stopping": false,
+    "encoder_no_repeat_ngram_size": 0,
+    "eos_token_id": 2,
+    "exponential_decay_length_penalty": null,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "gelu",
+    "hidden_dropout_prob": 0.1,
+    "hidden_size": 1024,
+    "id2label": {
+      "0": "O",
+      "1": "B-ORG",
+      "2": "I-ORG"
+    },
+    "initializer_range": 0.02,
+    "intermediate_size": 4096,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "B-ORG": 1,
+      "I-ORG": 2,
+      "O": 0
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+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "max_position_embeddings": 514,
+    "min_length": 0,
+    "model_type": "roberta",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 16,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_hidden_layers": 24,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": 1,
+    "position_embedding_type": "absolute",
+    "prefix": null,
+    "problem_type": null,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "suppress_tokens": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tf_legacy_loss": false,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.35.2",
+    "type_vocab_size": 1,
+    "typical_p": 1.0,
+    "use_bfloat16": false,
+    "use_cache": true,
+    "vocab_size": 50272
+  },
+  "entity_max_length": 8,
+  "id2label": {
+    "0": "O",
+    "1": "ORG"
+  },
+  "id2reduced_id": {
+    "0": 0,
+    "1": 1,
+    "2": 1
+  },
+  "label2id": {
+    "O": 0,
+    "ORG": 1
+  },
+  "marker_max_length": 128,
+  "max_next_context": null,
+  "max_prev_context": null,
+  "model_max_length": 256,
+  "model_max_length_default": 512,
+  "model_type": "span-marker",
+  "span_marker_version": "1.5.0",
+  "torch_dtype": "float32",
+  "trained_with_document_context": false,
+  "transformers_version": "4.35.2",
+  "vocab_size": 50272
+}

model.safetensors

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+oid sha256:bfe655f4ab8839518363a8a93f738564a8e815995da6d29030c421b061c0d888
+size 1421532256

special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
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+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
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+      "single_word": false,
+      "special": true
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+}