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README.md

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+---
+library_name: span-marker
+tags:
+- span-marker
+- token-classification
+- ner
+- named-entity-recognition
+- generated_from_span_marker_trainer
+metrics:
+- precision
+- recall
+- f1
+widget:
+- text: 'In the 2017 publication "The Routledge Handbook of Collective Intentionality",
+    edited by Kirk Ludwig and Marija Jankovic, and released by Routledge, leading
+    scholars explored the complex concept of collective intentionality and its implications
+    for various disciplines, including philosophy, cognitive science, and social theory
+    . A thought-provoking 2015 article titled "The Uncivilization Thesis: A Critique"
+    by Megan Gittins, published in Environmental Ethics, offered a critical examination
+    of the controversial "uncivilization thesis" and its implications for our understanding
+    of the relationship between civilization and environmental sustainability.'
+- text: In the "The Selfish Gene", renowned biologist Richard Dawkins introduced the
+    revolutionary concept of the "selfish gene" in 1976, published by Oxford University
+    Press . This influential work challenged traditional views of evolution and sparked
+    widespread discussions about the nature of altruism and cooperation . Fans of
+    science writing might appreciate "A Short History of Nearly Everything" by Bill
+    Bryson, a captivating exploration of the vast realms of scientific knowledge published
+    by Broadway Books in 2003.
+- text: '"The Pragmatic Turn" (2020, University of Pennsylvania Press) provides key
+    insights into pragmatist philosophy, edited by John J. Stuhr . For provocative
+    science, try "Introducing Consciousness", Alex Westrin and Vidyut Lokhande''s
+    2018 work published via Icon Books, challenging dominant models of self-awareness.'
+- text: Have you read "The Selfish Gene" by Richard Dawkins? Published in 1976 by
+    Oxford University Press, this seminal work introduced the gene-centric view of
+    evolution and proposed the controversial concept of the "extended phenotype ."
+    Dawkins' ideas sparked intense debates and influenced diverse fields like evolutionary
+    biology, psychology, and memetics . Daniel C. Dennett's "Darwin's Dangerous Idea"
+    (1995, Simon & Schuster) is another must-read that explores the far-reaching implications
+    of evolutionary theory, from the origins of life to the nature of human consciousness
+    and free will.
+- text: '"The Sociology of Philosophies", an insightful book penned by Randall Collins
+    and published in 1998 by Harvard University Press, examined the social factors
+    that influence the development and trajectory of philosophical thought throughout
+    history . Collins'' analysis shed light on how philosophical ideas are shaped
+    by the broader cultural, political, and intellectual contexts in which they emerge
+    . In a 2012 article from Philosophy of the Social Sciences, titled "The Relevance
+    of the Sociology of Philosophy", Isaac Reed further expounded on the importance
+    of this interdisciplinary approach, highlighting its potential to deepen our understanding
+    of the dynamics that shape human knowledge and inquiry.'
+pipeline_tag: token-classification
+model-index:
+- name: SpanMarker
+  results:
+  - task:
+      type: token-classification
+      name: Named Entity Recognition
+    dataset:
+      name: Unknown
+      type: unknown
+      split: eval
+    metrics:
+    - type: f1
+      value: 0.0
+      name: F1
+    - type: precision
+      value: 0.0
+      name: Precision
+    - type: recall
+      value: 0.0
+      name: Recall
+---
+
+# SpanMarker
+
+This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition.
+
+## Model Details
+
+### Model Description
+- **Model Type:** SpanMarker
+<!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
+- **Maximum Sequence Length:** 512 tokens
+- **Maximum Entity Length:** 16 words
+<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### 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                                                                                                                                      |
+|:-----------------|:----------------------------------------------------------------------------------------------------------------------------------------------|
+| person           | "Barney Glaser", "Malcolm Gladwell", "Charles Duhigg"                                                                                         |
+| publication_date | "2000", "1967", "2018"                                                                                                                        |
+| publisher        | "Little , Brown and Company", "Sociology Press", "Avery"                                                                                      |
+| work_of_art      | "`` The Tipping Point : How Little Things Can Make a Big Difference ''", "`` The Power of Habit ''", "`` The Discovery of Grounded Theory ''" |
+
+## Evaluation
+
+### Metrics
+| Label            | Precision | Recall | F1  |
+|:-----------------|:----------|:-------|:----|
+| **all**          | 0.0       | 0.0    | 0.0 |
+| person           | 0.0       | 0.0    | 0.0 |
+| publication_date | 0.0       | 0.0    | 0.0 |
+| publisher        | 0.0       | 0.0    | 0.0 |
+| work_of_art      | 0.0       | 0.0    | 0.0 |
+
+## Uses
+
+### Direct Use for Inference
+
+```python
+from span_marker import SpanMarkerModel
+
+# Download from the 🤗 Hub
+model = SpanMarkerModel.from_pretrained("span_marker_model_id")
+# Run inference
+entities = model.predict("\"The Pragmatic Turn\" (2020, University of Pennsylvania Press) provides key insights into pragmatist philosophy, edited by John J. Stuhr . For provocative science, try \"Introducing Consciousness\", Alex Westrin and Vidyut Lokhande's 2018 work published via Icon Books, challenging dominant models of self-awareness.")
+```
+
+### 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("span_marker_model_id")
+
+# 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("span_marker_model_id-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       | 47  | 104.6034 | 200 |
+| Entities per sentence | 3   | 4.0036   | 5   |
+
+### Training Hyperparameters
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training Results
+| Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
+|:-----:|:----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
+| 1.0   | 563  | 0.0206          | 0.0                  | 0.0               | 0.0           | 0.8513              |
+| 2.0   | 1126 | 0.0173          | 0.0                  | 0.0               | 0.0           | 0.8513              |
+| 3.0   | 1689 | 0.0162          | 0.0                  | 0.0               | 0.0           | 0.8513              |
+
+### Framework Versions
+- Python: 3.10.13
+- SpanMarker: 1.5.1.dev
+- Transformers: 4.39.3
+- PyTorch: 2.1.2
+- Datasets: 2.16.0
+- 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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+{
+  "<end>": 30523,
+  "<start>": 30522
+}

config.json

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+{
+  "architectures": [
+    "SpanMarkerModel"
+  ],
+  "encoder": {
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+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_probs_dropout_prob": 0.1,
+    "bad_words_ids": null,
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+    "diversity_penalty": 0.0,
+    "do_sample": false,
+    "early_stopping": false,
+    "encoder_no_repeat_ngram_size": 0,
+    "eos_token_id": null,
+    "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": 128,
+    "id2label": {
+      "0": "O",
+      "1": "B-publication_date",
+      "2": "I-publication_date",
+      "3": "B-person",
+      "4": "I-person",
+      "5": "B-work_of_art",
+      "6": "I-work_of_art",
+      "7": "B-publisher",
+      "8": "I-publisher"
+    },
+    "initializer_range": 0.02,
+    "intermediate_size": 512,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "B-person": 3,
+      "B-publication_date": 1,
+      "B-publisher": 7,
+      "B-work_of_art": 5,
+      "I-person": 4,
+      "I-publication_date": 2,
+      "I-publisher": 8,
+      "I-work_of_art": 6,
+      "O": 0
+    },
+    "layer_norm_eps": 1e-12,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "max_position_embeddings": 512,
+    "min_length": 0,
+    "model_type": "bert",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 2,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_hidden_layers": 2,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": 0,
+    "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": "4.39.3",
+    "type_vocab_size": 2,
+    "typical_p": 1.0,
+    "use_bfloat16": false,
+    "use_cache": true,
+    "vocab_size": 30528
+  },
+  "entity_max_length": 16,
+  "id2label": {
+    "0": "O",
+    "1": "person",
+    "2": "publication_date",
+    "3": "publisher",
+    "4": "work_of_art"
+  },
+  "id2reduced_id": {
+    "0": 0,
+    "1": 2,
+    "2": 2,
+    "3": 1,
+    "4": 1,
+    "5": 4,
+    "6": 4,
+    "7": 3,
+    "8": 3
+  },
+  "label2id": {
+    "O": 0,
+    "person": 1,
+    "publication_date": 2,
+    "publisher": 3,
+    "work_of_art": 4
+  },
+  "marker_max_length": 128,
+  "max_next_context": null,
+  "max_prev_context": null,
+  "model_max_length": 512,
+  "model_max_length_default": 512,
+  "model_type": "span-marker",
+  "span_marker_version": "1.5.1.dev",
+  "torch_dtype": "float32",
+  "trained_with_document_context": false,
+  "transformers_version": "4.39.3",
+  "vocab_size": 30528
+}

model.safetensors

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
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+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "30523": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "entity_max_length": 16,
+  "marker_max_length": 128,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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