Update README.md

README.md

@@ -3,197 +3,226 @@ library_name: transformers
 tags: []
 ---
 
-# Model Card for Model ID
+norbert3-small trained on wikiann (fo/is), sucx3 (se), dane (da) and norne (nb/nn)
+
+added a custom clf head along with a character-level cnn for adding a tiny extra signal for the classification.
+
+results:
+```css
+Eval on wikiann - fo
+index                                  0
+tokens      [Byrta, -, Aftur, og, aftur]
+ner_tags                 [3, 0, 0, 0, 0]
+subset                                fo
+dataset                          wikiann
+Name: 0, dtype: object
+shape: (100, 5)
+100%
+ 5/5 [00:01<00:00,  3.92it/s]
+Loss: 0.2276667356491089
+O	O
+B-ORG	B-ORG
+B-ORG	B-ORG
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+Validation Loss: 0.26530784368515015
+Validation Accuracy: 0.9228951181745751
+              precision    recall  f1-score   support
+
+         LOC       0.86      0.81      0.83       154
+         ORG       0.67      0.73      0.70       125
+         PER       0.87      0.91      0.89        79
+
+   micro avg       0.79      0.80      0.80       358
+   macro avg       0.80      0.82      0.81       358
+weighted avg       0.79      0.80      0.80       358
+
+________________________________________
+Eval on wikiann - is
+index                                                 100
+tokens      [Beltaþyrill, ''Ceryle, alcyon, '', Sjaldséð]
+ner_tags                                  [5, 0, 0, 0, 0]
+subset                                                 is
+dataset                                           wikiann
+Name: 0, dtype: object
+shape: (1000, 5)
+100%
+ 50/50 [00:10<00:00,  5.02it/s]
+Loss: 0.22668001055717468
+O	O
+B-LOC	B-LOC
+B-LOC	B-LOC
+B-LOC	B-LOC
+B-LOC	B-LOC
+B-LOC	B-LOC
+B-LOC	B-LOC
+O	O
+O	O
+O	O
+Validation Loss: 0.2526825902983546
+Validation Accuracy: 0.9360383541181041
+              precision    recall  f1-score   support
+
+         LOC       0.84      0.85      0.84      1983
+         ORG       0.81      0.80      0.80      1762
+         PER       0.89      0.89      0.89      1020
+
+   micro avg       0.84      0.84      0.84      4765
+   macro avg       0.84      0.85      0.85      4765
+weighted avg       0.84      0.84      0.84      4765
+
+________________________________________
+Eval on dane - default
+index                                                    1100
+tokens      [To, kendte, russiske, historikere, Andronik, ...
+ner_tags    [0, 0, 7, 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 5, 0, ...
+subset                                                default
+dataset                                                  dane
+Name: 0, dtype: object
+shape: (565, 5)
+100%
+ 29/29 [00:06<00:00,  4.75it/s]
+Loss: 0.12037135660648346
+O	O
+O	O
+O	O
+O	O
+O	O
+B-MISC	B-MISC
+O	O
+O	O
+B-PER	B-PER
+B-PER	B-PER
+Validation Loss: 0.11113663488228259
+Validation Accuracy: 0.972018408457994
+              precision    recall  f1-score   support
+
+         LOC       0.78      0.86      0.82       225
+        MISC       0.72      0.52      0.61       333
+         ORG       0.72      0.69      0.71       379
+         PER       0.96      0.92      0.94       298
+
+   micro avg       0.80      0.73      0.76      1235
+   macro avg       0.80      0.75      0.77      1235
+weighted avg       0.79      0.73      0.76      1235
+
+________________________________________
+Eval on norne - bokmaal-7
+index                                                    1665
+tokens      [Honnørordene, er, ", dristig, formspråk, ", ,...
+ner_tags     [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+subset                                              bokmaal-7
+dataset                                                 norne
+Name: 0, dtype: object
+shape: (1939, 5)
+100%
+ 97/97 [00:20<00:00,  4.56it/s]
+Loss: 0.0011819382198154926
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+Validation Loss: 0.04194018930858649
+Validation Accuracy: 0.9876322465792248
+              precision    recall  f1-score   support
+
+         LOC       0.85      0.90      0.87       498
+        MISC       0.81      0.74      0.78       363
+         ORG       0.77      0.83      0.80       499
+         PER       0.93      0.96      0.95       845
+
+   micro avg       0.86      0.88      0.87      2205
+   macro avg       0.84      0.86      0.85      2205
+weighted avg       0.86      0.88      0.87      2205
+
+________________________________________
+Eval on norne - nynorsk-7
+index                                                    3604
+tokens      [Den, er, mettande, og, smakfull, ,, og, det, ...
+ner_tags    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
+subset                                              nynorsk-7
+dataset                                                 norne
+Name: 0, dtype: object
+shape: (1511, 5)
+100%
+ 76/76 [00:15<00:00,  5.82it/s]
+Loss: 0.0790824368596077
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+O	O
+Validation Loss: 0.05325472676725583
+Validation Accuracy: 0.9867293689853402
+              precision    recall  f1-score   support
+
+         LOC       0.77      0.91      0.84       365
+        MISC       0.80      0.76      0.78       295
+         ORG       0.83      0.82      0.82       397
+         PER       0.98      0.95      0.97       664
+
+   micro avg       0.87      0.88      0.87      1721
+   macro avg       0.85      0.86      0.85      1721
+weighted avg       0.87      0.88      0.87      1721
+
+________________________________________
+Eval on sucx3_ner - original_cased
+index                                                    5115
+tokens      [Just, i, dag, är, Saabs, företagsledning, där...
+ner_tags    [0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
+subset                                         original_cased
+dataset                                             sucx3_ner
+Name: 0, dtype: object
+shape: (14383, 5)
+100%
+ 720/720 [02:36<00:00,  5.02it/s]
+Loss: 0.04177908971905708
+Loss: 0.08230985613484489
+Loss: 0.08399457804886486
+Loss: 0.06163447560524267
+Loss: 0.04787629511204947
+Loss: 0.03949779063830233
+Loss: 0.03397762095776484
+Loss: 0.030040143460689266
+O	O
+O	O
+O	O
+O	O
+O	O
+B-ORG	B-ORG
+B-ORG	B-ORG
+O	O
+O	O
+O	O
+Validation Loss: 0.02938824465528948
+Validation Accuracy: 0.9919830972756728
+              precision    recall  f1-score   support
+
+         LOC       0.88      0.91      0.90      4202
+        MISC       0.65      0.59      0.62      1899
+         ORG       0.74      0.76      0.75      3015
+         PER       0.92      0.93      0.92      5778
+
+   micro avg       0.84      0.84      0.84     14894
+   macro avg       0.80      0.80      0.80     14894
+weighted avg       0.84      0.84      0.84     14894
+
+________________________________________
+```
 
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]