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# electra-small-discriminator-finetuned-ner-cadec

This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3089
- Precision: 0.5240
- Recall: 0.6280
- F1: 0.5713
- Accuracy: 0.9120
- Adr Precision: 0.4580
- Adr Recall: 0.6495
- Adr F1: 0.5372
- Disease Precision: 0.0
- Disease Recall: 0.0
- Disease F1: 0.0
- Drug Precision: 0.8187
- Drug Recall: 0.9030
- Drug F1: 0.8588
- Finding Precision: 0.0
- Finding Recall: 0.0
- Finding F1: 0.0
- Symptom Precision: 0.0
- Symptom Recall: 0.0
- Symptom F1: 0.0
- B-adr Precision: 0.6345
- B-adr Recall: 0.8196
- B-adr F1: 0.7152
- B-disease Precision: 0.0
- B-disease Recall: 0.0
- B-disease F1: 0.0
- B-drug Precision: 0.8902
- B-drug Recall: 0.9333
- B-drug F1: 0.9112
- B-finding Precision: 0.0
- B-finding Recall: 0.0
- B-finding F1: 0.0
- B-symptom Precision: 0.0
- B-symptom Recall: 0.0
- B-symptom F1: 0.0
- I-adr Precision: 0.4753
- I-adr Recall: 0.6380
- I-adr F1: 0.5448
- I-disease Precision: 0.0
- I-disease Recall: 0.0
- I-disease F1: 0.0
- I-drug Precision: 0.8371
- I-drug Recall: 0.9030
- I-drug F1: 0.8688
- I-finding Precision: 0.6667
- I-finding Recall: 0.0625
- I-finding F1: 0.1143
- I-symptom Precision: 0.0
- I-symptom Recall: 0.0
- I-symptom F1: 0.0
- Macro Avg F1: 0.3154
- Weighted Avg F1: 0.6288

## 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  | 0.5920          | 0.2042    | 0.1710 | 0.1861 | 0.8334   | 0.2042        | 0.2514     | 0.2253 | 0.0               | 0.0            | 0.0        | 0.0            | 0.0         | 0.0     | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.1667          | 0.0038       | 0.0075   | 0.0                 | 0.0              | 0.0          | 0.0              | 0.0           | 0.0       | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.0238          | 0.0353       | 0.0285   | 0.0                 | 0.0              | 0.0          | 0.0              | 0.0           | 0.0       | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.0036       | 0.0115          |
| No log        | 2.0   | 254  | 0.4272          | 0.4122    | 0.4806 | 0.4438 | 0.8895   | 0.3547        | 0.5376     | 0.4274 | 0.0               | 0.0            | 0.0        | 0.8519         | 0.5576      | 0.6740  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.5794          | 0.7351       | 0.6481   | 0.0                 | 0.0              | 0.0          | 0.9709           | 0.6061        | 0.7463    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.3556          | 0.5055       | 0.4175   | 0.0                 | 0.0              | 0.0          | 0.9588           | 0.5636        | 0.7099    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2522       | 0.5261          |
| No log        | 3.0   | 381  | 0.3799          | 0.4580    | 0.5918 | 0.5163 | 0.8982   | 0.4002        | 0.6294     | 0.4893 | 0.0               | 0.0            | 0.0        | 0.7360         | 0.7939      | 0.7638  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.5794          | 0.7985       | 0.6715   | 0.0                 | 0.0              | 0.0          | 0.8758           | 0.8545        | 0.8650    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4018          | 0.5960       | 0.4800   | 0.0                 | 0.0              | 0.0          | 0.7870           | 0.8061        | 0.7964    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2813       | 0.5771          |
| 0.6133        | 4.0   | 508  | 0.3578          | 0.4755    | 0.6067 | 0.5332 | 0.9007   | 0.4097        | 0.6330     | 0.4975 | 0.0               | 0.0            | 0.0        | 0.7833         | 0.8545      | 0.8174  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.5840          | 0.8273       | 0.6847   | 0.0                 | 0.0              | 0.0          | 0.8862           | 0.8970        | 0.8916    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4169          | 0.6093       | 0.4951   | 0.0                 | 0.0              | 0.0          | 0.8372           | 0.8727        | 0.8546    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2926       | 0.5961          |
| 0.6133        | 5.0   | 635  | 0.3254          | 0.5124    | 0.6180 | 0.5603 | 0.9079   | 0.4476        | 0.6422     | 0.5275 | 0.0               | 0.0            | 0.0        | 0.7880         | 0.8788      | 0.8309  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6197          | 0.8100       | 0.7022   | 0.0                 | 0.0              | 0.0          | 0.8613           | 0.9030        | 0.8817    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4663          | 0.6269       | 0.5348   | 0.0                 | 0.0              | 0.0          | 0.8066           | 0.8848        | 0.8439    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2963       | 0.6124          |
| 0.6133        | 6.0   | 762  | 0.3153          | 0.5272    | 0.6180 | 0.5690 | 0.9114   | 0.4624        | 0.6422     | 0.5376 | 0.0               | 0.0            | 0.0        | 0.7967         | 0.8788      | 0.8357  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6353          | 0.8023       | 0.7091   | 0.0                 | 0.0              | 0.0          | 0.8779           | 0.9152        | 0.8961    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4649          | 0.6137       | 0.5290   | 0.0                 | 0.0              | 0.0          | 0.8249           | 0.8848        | 0.8538    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2988       | 0.6158          |
| 0.6133        | 7.0   | 889  | 0.3095          | 0.5341    | 0.6155 | 0.5719 | 0.9126   | 0.4658        | 0.6367     | 0.5380 | 0.0               | 0.0            | 0.0        | 0.8202         | 0.8848      | 0.8513  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6453          | 0.7927       | 0.7115   | 0.0                 | 0.0              | 0.0          | 0.8935           | 0.9152        | 0.9042    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4714          | 0.6181       | 0.5349   | 0.0                 | 0.0              | 0.0          | 0.8448           | 0.8909        | 0.8673    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.3018       | 0.6209          |
| 0.3074        | 8.0   | 1016 | 0.3080          | 0.5292    | 0.6217 | 0.5718 | 0.9121   | 0.4604        | 0.6404     | 0.5357 | 0.0               | 0.0            | 0.0        | 0.8324         | 0.9030      | 0.8663  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6397          | 0.8042       | 0.7126   | 0.0                 | 0.0              | 0.0          | 0.8947           | 0.9273        | 0.9107    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4792          | 0.6358       | 0.5465   | 0.0                 | 0.0              | 0.0          | 0.8418           | 0.9030        | 0.8713    | 0.5                 | 0.0312           | 0.0588       | 0.0                 | 0.0              | 0.0          | 0.3100       | 0.6274          |
| 0.3074        | 9.0   | 1143 | 0.3072          | 0.5225    | 0.6230 | 0.5683 | 0.9119   | 0.4583        | 0.6459     | 0.5362 | 0.0               | 0.0            | 0.0        | 0.8077         | 0.8909      | 0.8473  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6415          | 0.8138       | 0.7174   | 0.0                 | 0.0              | 0.0          | 0.8882           | 0.9152        | 0.9015    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4690          | 0.6336       | 0.5390   | 0.0                 | 0.0              | 0.0          | 0.8362           | 0.8970        | 0.8655    | 0.3333              | 0.0312           | 0.0571       | 0.0                 | 0.0              | 0.0          | 0.3081       | 0.6250          |
| 0.3074        | 10.0  | 1270 | 0.3089          | 0.5240    | 0.6280 | 0.5713 | 0.9120   | 0.4580        | 0.6495     | 0.5372 | 0.0               | 0.0            | 0.0        | 0.8187         | 0.9030      | 0.8588  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.6345          | 0.8196       | 0.7152   | 0.0                 | 0.0              | 0.0          | 0.8902           | 0.9333        | 0.9112    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.4753          | 0.6380       | 0.5448   | 0.0                 | 0.0              | 0.0          | 0.8371           | 0.9030        | 0.8688    | 0.6667              | 0.0625           | 0.1143       | 0.0                 | 0.0              | 0.0          | 0.3154       | 0.6288          |


### 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-small-discriminator", "model-index": [{"name": "electra-small-discriminator-finetuned-ner-cadec", "results": []}]}
transformers tensorboard safetensors electra token-classification generated_from_trainer base_model:google/electra-small-discriminator license:apache-2.0 autotrain_compatible endpoints_compatible region:us