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# distilbert-base-uncased-finetuned-ner-cadec

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4315
- Precision: 0.3648
- Recall: 0.3333
- F1: 0.3483
- Accuracy: 0.8708
- Adr Precision: 0.2667
- Adr Recall: 0.2716
- Adr F1: 0.2691
- Disease Precision: 0.0
- Disease Recall: 0.0
- Disease F1: 0.0
- Drug Precision: 0.7483
- Drug Recall: 0.6848
- Drug F1: 0.7152
- Finding Precision: 0.25
- Finding Recall: 0.0222
- Finding F1: 0.0408
- Symptom Precision: 0.3333
- Symptom Recall: 0.1852
- Symptom F1: 0.2381
- B-adr Precision: 0.5655
- B-adr Recall: 0.4472
- B-adr F1: 0.4995
- B-disease Precision: 0.0
- B-disease Recall: 0.0
- B-disease F1: 0.0
- B-drug Precision: 0.8768
- B-drug Recall: 0.7333
- B-drug F1: 0.7987
- B-finding Precision: 1.0
- B-finding Recall: 0.0222
- B-finding F1: 0.0435
- B-symptom Precision: 0.4167
- B-symptom Recall: 0.2
- B-symptom F1: 0.2703
- I-adr Precision: 0.2236
- I-adr Recall: 0.2009
- I-adr F1: 0.2117
- I-disease Precision: 0.0
- I-disease Recall: 0.0
- I-disease F1: 0.0
- I-drug Precision: 0.8
- I-drug Recall: 0.6871
- I-drug F1: 0.7393
- I-finding Precision: 0.0
- I-finding Recall: 0.0
- I-finding F1: 0.0
- I-symptom Precision: 0.0
- I-symptom Recall: 0.0
- I-symptom F1: 0.0
- Macro Avg F1: 0.2563
- Weighted Avg F1: 0.4250

## 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  | 0.5842          | 0.3290    | 0.1573 | 0.2128 | 0.8274   | 0.1197        | 0.0624     | 0.0820 | 0.0               | 0.0            | 0.0        | 0.9293         | 0.5576      | 0.6970  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.4157          | 0.0710       | 0.1213   | 0.0                 | 0.0              | 0.0          | 1.0              | 0.0667        | 0.125     | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.0383          | 0.0203       | 0.0265   | 0.0                 | 0.0              | 0.0          | 0.1212           | 0.0736        | 0.0916    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.0364       | 0.0764          |
| No log        | 2.0   | 254  | 0.5137          | 0.2948    | 0.1910 | 0.2318 | 0.8476   | 0.1337        | 0.1028     | 0.1162 | 0.0               | 0.0            | 0.0        | 0.97           | 0.5879      | 0.7321  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.4724          | 0.2303       | 0.3097   | 0.0                 | 0.0              | 0.0          | 0.9899           | 0.5939        | 0.7424    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.1053          | 0.0587       | 0.0754   | 0.0                 | 0.0              | 0.0          | 0.97             | 0.5951        | 0.7376    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.1865       | 0.3023          |
| No log        | 3.0   | 381  | 0.4805          | 0.3057    | 0.2022 | 0.2434 | 0.8500   | 0.1487        | 0.1138     | 0.1289 | 0.0               | 0.0            | 0.0        | 0.8850         | 0.6061      | 0.7194  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.5417          | 0.1747       | 0.2642   | 0.0                 | 0.0              | 0.0          | 0.9623           | 0.6182        | 0.7528    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.0851          | 0.0632       | 0.0725   | 0.0                 | 0.0              | 0.0          | 0.9252           | 0.6074        | 0.7333    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.1823       | 0.2858          |
| 0.5965        | 4.0   | 508  | 0.4963          | 0.3717    | 0.2260 | 0.2811 | 0.8570   | 0.2174        | 0.1468     | 0.1752 | 0.0               | 0.0            | 0.0        | 0.8487         | 0.6121      | 0.7113  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.5853          | 0.2438       | 0.3442   | 0.0                 | 0.0              | 0.0          | 0.9630           | 0.6303        | 0.7619    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.1641          | 0.0948       | 0.1202   | 0.0                 | 0.0              | 0.0          | 0.9107           | 0.6258        | 0.7418    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.1968       | 0.3312          |
| 0.5965        | 5.0   | 635  | 0.4448          | 0.3323    | 0.2759 | 0.3015 | 0.8619   | 0.2239        | 0.2165     | 0.2201 | 0.0               | 0.0            | 0.0        | 0.7574         | 0.6242      | 0.6844  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.5827          | 0.3109       | 0.4055   | 0.0                 | 0.0              | 0.0          | 0.9561           | 0.6606        | 0.7814    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.1314          | 0.1219       | 0.1265   | 0.0                 | 0.0              | 0.0          | 0.8031           | 0.6258        | 0.7034    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2017       | 0.3531          |
| 0.5965        | 6.0   | 762  | 0.4285          | 0.3672    | 0.3021 | 0.3315 | 0.8682   | 0.2553        | 0.2440     | 0.2495 | 0.0               | 0.0            | 0.0        | 0.7970         | 0.6424      | 0.7114  | 0.0               | 0.0            | 0.0        | 0.6               | 0.1111         | 0.1875     | 0.6210          | 0.3743       | 0.4671   | 0.0                 | 0.0              | 0.0          | 0.9569           | 0.6727        | 0.7900    | 0.0                 | 0.0              | 0.0          | 0.6                 | 0.12             | 0.2000       | 0.1641          | 0.1445       | 0.1537   | 0.0                 | 0.0              | 0.0          | 0.8254           | 0.6380        | 0.7197    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2330       | 0.3898          |
| 0.5965        | 7.0   | 889  | 0.4268          | 0.3582    | 0.3233 | 0.3399 | 0.8701   | 0.2531        | 0.2624     | 0.2577 | 0.0               | 0.0            | 0.0        | 0.7832         | 0.6788      | 0.7273  | 0.0               | 0.0            | 0.0        | 0.4444            | 0.1481         | 0.2222     | 0.5707          | 0.4338       | 0.4929   | 0.0                 | 0.0              | 0.0          | 0.9268           | 0.6909        | 0.7917    | 0.0                 | 0.0              | 0.0          | 0.5714              | 0.16             | 0.25         | 0.1932          | 0.1783       | 0.1854   | 0.0                 | 0.0              | 0.0          | 0.7698           | 0.6564        | 0.7086    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2429       | 0.4087          |
| 0.3701        | 8.0   | 1016 | 0.4297          | 0.3723    | 0.3221 | 0.3454 | 0.8725   | 0.2606        | 0.2606     | 0.2606 | 0.0               | 0.0            | 0.0        | 0.8175         | 0.6788      | 0.7417  | 0.0               | 0.0            | 0.0        | 0.5               | 0.1481         | 0.2286     | 0.5805          | 0.4223       | 0.4889   | 0.0                 | 0.0              | 0.0          | 0.9370           | 0.7212        | 0.8151    | 0.0                 | 0.0              | 0.0          | 0.5714              | 0.16             | 0.25         | 0.2020          | 0.1828       | 0.1919   | 0.0                 | 0.0              | 0.0          | 0.8358           | 0.6871        | 0.7542    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2500       | 0.4170          |
| 0.3701        | 9.0   | 1143 | 0.4345          | 0.3688    | 0.3333 | 0.3502 | 0.8717   | 0.2648        | 0.2716     | 0.2681 | 0.0               | 0.0            | 0.0        | 0.7958         | 0.6848      | 0.7362  | 0.3333            | 0.0222         | 0.0417     | 0.3571            | 0.1852         | 0.2439     | 0.5566          | 0.4530       | 0.4995   | 0.0                 | 0.0              | 0.0          | 0.9023           | 0.7273        | 0.8054    | 1.0                 | 0.0222           | 0.0435       | 0.4167              | 0.2              | 0.2703       | 0.2173          | 0.1874       | 0.2012   | 0.0                 | 0.0              | 0.0          | 0.8235           | 0.6871        | 0.7492    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2569       | 0.4237          |
| 0.3701        | 10.0  | 1270 | 0.4315          | 0.3648    | 0.3333 | 0.3483 | 0.8708   | 0.2667        | 0.2716     | 0.2691 | 0.0               | 0.0            | 0.0        | 0.7483         | 0.6848      | 0.7152  | 0.25              | 0.0222         | 0.0408     | 0.3333            | 0.1852         | 0.2381     | 0.5655          | 0.4472       | 0.4995   | 0.0                 | 0.0              | 0.0          | 0.8768           | 0.7333        | 0.7987    | 1.0                 | 0.0222           | 0.0435       | 0.4167              | 0.2              | 0.2703       | 0.2236          | 0.2009       | 0.2117   | 0.0                 | 0.0              | 0.0          | 0.8              | 0.6871        | 0.7393    | 0.0                 | 0.0              | 0.0          | 0.0                 | 0.0              | 0.0          | 0.2563       | 0.4250          |


### 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": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncasedfinetuned-ner-cadec", "results": []}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us