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# electra-base-discriminator-finetuned-ner-cadec

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2903
- Precision: 0.6312
- Recall: 0.6966
- F1: 0.6623
- Accuracy: 0.9274
- Adr Precision: 0.6070
- Adr Recall: 0.6972
- Adr F1: 0.6490
- Disease Precision: 0.125
- Disease Recall: 0.1579
- Disease F1: 0.1395
- Drug Precision: 0.9464
- Drug Recall: 0.9636
- Drug F1: 0.9550
- Finding Precision: 0.1961
- Finding Recall: 0.2222
- Finding F1: 0.2083
- Symptom Precision: 0.4
- Symptom Recall: 0.2222
- Symptom F1: 0.2857
- B-adr Precision: 0.7540
- B-adr Recall: 0.8119
- B-adr F1: 0.7819
- B-disease Precision: 0.1667
- B-disease Recall: 0.1579
- B-disease F1: 0.1622
- B-drug Precision: 0.9760
- B-drug Recall: 0.9879
- B-drug F1: 0.9819
- B-finding Precision: 0.275
- B-finding Recall: 0.2444
- B-finding F1: 0.2588
- B-symptom Precision: 0.5
- B-symptom Recall: 0.24
- B-symptom F1: 0.3243
- I-adr Precision: 0.6175
- I-adr Recall: 0.7020
- I-adr F1: 0.6570
- I-disease Precision: 0.15
- I-disease Recall: 0.2308
- I-disease F1: 0.1818
- I-drug Precision: 0.9521
- I-drug Recall: 0.9636
- I-drug F1: 0.9578
- I-finding Precision: 0.1622
- I-finding Recall: 0.1875
- I-finding F1: 0.1739
- I-symptom Precision: 0.5
- I-symptom Recall: 0.15
- I-symptom F1: 0.2308
- Macro Avg F1: 0.4710
- Weighted Avg F1: 0.7273

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Adr Precision | Adr Recall | Adr F1 | Disease Precision | Disease Recall | Disease F1 | Drug Precision | Drug Recall | Drug F1 | Finding Precision | Finding Recall | Finding F1 | Symptom Precision | Symptom Recall | Symptom F1 | B-adr Precision | B-adr Recall | B-adr F1 | B-disease Precision | B-disease Recall | B-disease F1 | B-drug Precision | B-drug Recall | B-drug F1 | B-finding Precision | B-finding Recall | B-finding F1 | B-symptom Precision | B-symptom Recall | B-symptom F1 | I-adr Precision | I-adr Recall | I-adr F1 | I-disease Precision | I-disease Recall | I-disease F1 | I-drug Precision | I-drug Recall | I-drug F1 | I-finding Precision | I-finding Recall | I-finding F1 | I-symptom Precision | I-symptom Recall | I-symptom F1 | Macro Avg F1 | Weighted Avg F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|:------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------:|:-------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:------------:|:---------------:|
| No log        | 1.0   | 127  | 0.2748          | 0.5316    | 0.6617 | 0.5895 | 0.9167   | 0.4583        | 0.6862     | 0.5496 | 0.0               | 0.0            | 0.0        | 0.8619         | 0.9455      | 0.9017  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6301          | 0.8369       | 0.7189   | 0.0                 | 0.0              | 0.0          | 0.9527           | 0.9758        | 0.9641    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4811          | 0.6755       | 0.5620   | 0.0                 | 0.0              | 0.0          | 0.8674           | 0.9515        | 0.9075    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.3152       | 0.6433          |
| No log        | 2.0   | 254  | 0.2396          | 0.5670    | 0.6604 | 0.6101 | 0.9205   | 0.5198        | 0.6752     | 0.5874 | 0.0625            | 0.1053         | 0.0784     | 0.9349         | 0.9576      | 0.9461  | 0.0417            | 0.0222         | 0.0290     | 0.0               | 0.0            | 0.0        | 0.6992          | 0.8119       | 0.7513   | 0.3077              | 0.2105           | 0.25         | 0.9759           | 0.9818        | 0.9789    | 0.3333              | 0.0444           | 0.0784       | 0.0                 | 0.0              | 0.0          | 0.5524          | 0.6865       | 0.6122   | 0.0690              | 0.1538           | 0.0952       | 0.9405           | 0.9576        | 0.9489    | 0.25                | 0.1875           | 0.2143       | 0.0                 | 0.0              | 0.0          | 0.3929       | 0.6881          |
| No log        | 3.0   | 381  | 0.2432          | 0.6237    | 0.6767 | 0.6491 | 0.9273   | 0.5965        | 0.6972     | 0.6430 | 0.1163            | 0.2632         | 0.1613     | 0.9006         | 0.9333      | 0.9167  | 0.1667            | 0.0667         | 0.0952     | 0.0               | 0.0            | 0.0        | 0.7559          | 0.8023       | 0.7784   | 0.1786              | 0.2632           | 0.2128       | 0.9702           | 0.9879        | 0.9790    | 0.2667              | 0.0889           | 0.1333       | 0.0                 | 0.0              | 0.0          | 0.6216          | 0.7108       | 0.6632   | 0.1951              | 0.6154           | 0.2963       | 0.9112           | 0.9333        | 0.9222    | 0.1429              | 0.0312           | 0.0513       | 0.0                 | 0.0              | 0.0          | 0.4036       | 0.7100          |
| 0.2876        | 4.0   | 508  | 0.2490          | 0.6259    | 0.6829 | 0.6531 | 0.9254   | 0.5981        | 0.6936     | 0.6423 | 0.0833            | 0.1053         | 0.0930     | 0.9286         | 0.9455      | 0.9369  | 0.2083            | 0.2222         | 0.2151     | 0.5               | 0.0370         | 0.0690     | 0.7425          | 0.8023       | 0.7712   | 0.1905              | 0.2105           | 0.2          | 0.9760           | 0.9879        | 0.9819    | 0.3226              | 0.2222           | 0.2632       | 0.5                 | 0.04             | 0.0741       | 0.6112          | 0.6976       | 0.6515   | 0.1429              | 0.1538           | 0.1481       | 0.9341           | 0.9455        | 0.9398    | 0.2368              | 0.2812           | 0.2571       | 0.0                 | 0.0              | 0.0          | 0.4287       | 0.7145          |
| 0.2876        | 5.0   | 635  | 0.2609          | 0.6175    | 0.6854 | 0.6497 | 0.9255   | 0.5915        | 0.6936     | 0.6385 | 0.0851            | 0.2105         | 0.1212     | 0.9412         | 0.9697      | 0.9552  | 0.1481            | 0.0889         | 0.1111     | 0.5               | 0.1111         | 0.1818     | 0.7336          | 0.8138       | 0.7716   | 0.125               | 0.2105           | 0.1569       | 0.9760           | 0.9879        | 0.9819    | 0.2174              | 0.1111           | 0.1471       | 0.5                 | 0.12             | 0.1935       | 0.6109          | 0.6932       | 0.6494   | 0.1860              | 0.6154           | 0.2857       | 0.9467           | 0.9697        | 0.9581    | 0.1                 | 0.0312           | 0.0476       | 0.0                 | 0.0              | 0.0          | 0.4192       | 0.7105          |
| 0.2876        | 6.0   | 762  | 0.2648          | 0.6192    | 0.6941 | 0.6545 | 0.9254   | 0.5938        | 0.7028     | 0.6437 | 0.1111            | 0.1579         | 0.1304     | 0.9290         | 0.9515      | 0.9401  | 0.2083            | 0.2222         | 0.2151     | 0.3333            | 0.1111         | 0.1667     | 0.7388          | 0.8196       | 0.7771   | 0.1579              | 0.1579           | 0.1579       | 0.9702           | 0.9879        | 0.9790    | 0.3077              | 0.2667           | 0.2857       | 0.5556              | 0.2              | 0.2941       | 0.6120          | 0.6998       | 0.6529   | 0.1304              | 0.2308           | 0.1667       | 0.9345           | 0.9515        | 0.9429    | 0.1389              | 0.1562           | 0.1471       | 0.0                 | 0.0              | 0.0          | 0.4403       | 0.7187          |
| 0.2876        | 7.0   | 889  | 0.2722          | 0.6435    | 0.6941 | 0.6679 | 0.9280   | 0.6141        | 0.7009     | 0.6547 | 0.1364            | 0.1579         | 0.1463     | 0.9345         | 0.9515      | 0.9429  | 0.2326            | 0.2222         | 0.2273     | 0.4444            | 0.1481         | 0.2222     | 0.7567          | 0.8177       | 0.7860   | 0.1579              | 0.1579           | 0.1579       | 0.9760           | 0.9879        | 0.9819    | 0.2973              | 0.2444           | 0.2683       | 0.5                 | 0.16             | 0.2424       | 0.6206          | 0.6932       | 0.6548   | 0.1875              | 0.2308           | 0.2069       | 0.9401           | 0.9515        | 0.9458    | 0.2059              | 0.2188           | 0.2121       | 1.0                 | 0.1              | 0.1818       | 0.4638       | 0.7260          |
| 0.1075        | 8.0   | 1016 | 0.2843          | 0.6282    | 0.6941 | 0.6595 | 0.9253   | 0.5956        | 0.6917     | 0.6401 | 0.1364            | 0.1579         | 0.1463     | 0.9464         | 0.9636      | 0.9550  | 0.2245            | 0.2444         | 0.2340     | 0.4615            | 0.2222         | 0.3        | 0.7407          | 0.8061       | 0.7721   | 0.1667              | 0.1579           | 0.1622       | 0.9760           | 0.9879        | 0.9819    | 0.3158              | 0.2667           | 0.2892       | 0.5                 | 0.24             | 0.3243       | 0.5950          | 0.6777       | 0.6336   | 0.1579              | 0.2308           | 0.1875       | 0.9578           | 0.9636        | 0.9607    | 0.1579              | 0.1875           | 0.1714       | 0.75                | 0.15             | 0.2500       | 0.4733       | 0.7181          |
| 0.1075        | 9.0   | 1143 | 0.2876          | 0.6353    | 0.6916 | 0.6623 | 0.9266   | 0.5968        | 0.6899     | 0.64   | 0.15              | 0.1579         | 0.1538     | 0.9464         | 0.9636      | 0.9550  | 0.2439            | 0.2222         | 0.2326     | 0.4615            | 0.2222         | 0.3        | 0.7381          | 0.8061       | 0.7706   | 0.1667              | 0.1579           | 0.1622       | 0.9760           | 0.9879        | 0.9819    | 0.3143              | 0.2444           | 0.2750       | 0.5                 | 0.24             | 0.3243       | 0.6023          | 0.6821       | 0.6398   | 0.1875              | 0.2308           | 0.2069       | 0.9578           | 0.9636        | 0.9607    | 0.1875              | 0.1875           | 0.1875       | 1.0                 | 0.2              | 0.3333       | 0.4842       | 0.7207          |
| 0.1075        | 10.0  | 1270 | 0.2903          | 0.6312    | 0.6966 | 0.6623 | 0.9274   | 0.6070        | 0.6972     | 0.6490 | 0.125             | 0.1579         | 0.1395     | 0.9464         | 0.9636      | 0.9550  | 0.1961            | 0.2222         | 0.2083     | 0.4               | 0.2222         | 0.2857     | 0.7540          | 0.8119       | 0.7819   | 0.1667              | 0.1579           | 0.1622       | 0.9760           | 0.9879        | 0.9819    | 0.275               | 0.2444           | 0.2588       | 0.5                 | 0.24             | 0.3243       | 0.6175          | 0.7020       | 0.6570   | 0.15                | 0.2308           | 0.1818       | 0.9521           | 0.9636        | 0.9578    | 0.1622              | 0.1875           | 0.1739       | 0.5                 | 0.15             | 0.2308       | 0.4710       | 0.7273          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "google/electra-base-discriminator", "model-index": [{"name": "electra-base-discriminatorfinetuned-ner-cadec", "results": []}]}
transformers tensorboard safetensors electra token-classification generated_from_trainer base_model:google/electra-base-discriminator license:apache-2.0 autotrain_compatible endpoints_compatible region:us