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# bert-base-cased-finetuned-ner-cadec

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3476
- Precision: 0.5870
- Recall: 0.6866
- F1: 0.6329
- Accuracy: 0.9193
- Adr Precision: 0.5614
- Adr Recall: 0.6881
- Adr F1: 0.6183
- Disease Precision: 0.0
- Disease Recall: 0.0
- Disease F1: 0.0
- Drug Precision: 0.8988
- Drug Recall: 0.9152
- Drug F1: 0.9069
- Finding Precision: 0.2295
- Finding Recall: 0.3111
- Finding F1: 0.2642
- Symptom Precision: 0.4762
- Symptom Recall: 0.3704
- Symptom F1: 0.4167
- B-adr Precision: 0.7133
- B-adr Recall: 0.8119
- B-adr F1: 0.7594
- B-disease Precision: 0.0
- B-disease Recall: 0.0
- B-disease F1: 0.0
- B-drug Precision: 0.9639
- B-drug Recall: 0.9697
- B-drug F1: 0.9668
- B-finding Precision: 0.3469
- B-finding Recall: 0.3778
- B-finding F1: 0.3617
- B-symptom Precision: 0.7857
- B-symptom Recall: 0.44
- B-symptom F1: 0.5641
- I-adr Precision: 0.5799
- I-adr Recall: 0.6991
- I-adr F1: 0.6340
- I-disease Precision: 0.0
- I-disease Recall: 0.0
- I-disease F1: 0.0
- I-drug Precision: 0.9042
- I-drug Recall: 0.9152
- I-drug F1: 0.9096
- I-finding Precision: 0.2979
- I-finding Recall: 0.3684
- I-finding F1: 0.3294
- I-symptom Precision: 0.3333
- I-symptom Recall: 0.2
- I-symptom F1: 0.25
- Macro Avg F1: 0.4775
- Weighted Avg F1: 0.7087

## 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  | 0.2830          | 0.4796    | 0.6005 | 0.5333 | 0.9082   | 0.4248        | 0.6220     | 0.5048 | 0.0               | 0.0            | 0.0        | 0.7966         | 0.8545      | 0.8246  | 0.1               | 0.0222         | 0.0364     | 0.0               | 0.0            | 0.0        | 0.6122          | 0.7908       | 0.6901   | 0.0                 | 0.0              | 0.0          | 0.9157           | 0.9212        | 0.9184    | 0.5714              | 0.0889           | 0.1538       | 0.0                 | 0.0              | 0.0          | 0.4687          | 0.6472       | 0.5436   | 0.0556              | 0.0625           | 0.0588       | 0.8161           | 0.8606        | 0.8378    | 0.2857              | 0.0526           | 0.0889       | 0.0                 | 0.0              | 0.0          | 0.3291       | 0.6177          |
| No log        | 2.0   | 254  | 0.2472          | 0.5073    | 0.6092 | 0.5536 | 0.9125   | 0.4913        | 0.6183     | 0.5475 | 0.0227            | 0.0526         | 0.0317     | 0.8571         | 0.8727      | 0.8649  | 0.0984            | 0.1333         | 0.1132     | 0.0               | 0.0            | 0.0        | 0.7092          | 0.7582       | 0.7328   | 0.3333              | 0.0526           | 0.0909       | 0.9568           | 0.9394        | 0.9480    | 0.3542              | 0.3778           | 0.3656       | 0.0                 | 0.0              | 0.0          | 0.5275          | 0.6429       | 0.5795   | 0.0714              | 0.1875           | 0.1034       | 0.8788           | 0.8788        | 0.8788    | 0.1667              | 0.1316           | 0.1471       | 0.0                 | 0.0              | 0.0          | 0.3846       | 0.6615          |
| No log        | 3.0   | 381  | 0.2629          | 0.5733    | 0.6542 | 0.6111 | 0.9177   | 0.5495        | 0.6624     | 0.6007 | 0.075             | 0.1579         | 0.1017     | 0.8982         | 0.9091      | 0.9036  | 0.125             | 0.1111         | 0.1176     | 0.5               | 0.1852         | 0.2703     | 0.7105          | 0.7774       | 0.7424   | 0.2174              | 0.2632           | 0.2381       | 0.9578           | 0.9636        | 0.9607    | 0.2963              | 0.1778           | 0.2222       | 0.5                 | 0.2              | 0.2857       | 0.5783          | 0.6797       | 0.6249   | 0.0882              | 0.1875           | 0.12         | 0.9146           | 0.9091        | 0.9119    | 0.2609              | 0.1579           | 0.1967       | 0.0                 | 0.0              | 0.0          | 0.4303       | 0.6880          |
| 0.2709        | 4.0   | 508  | 0.2630          | 0.5877    | 0.6567 | 0.6203 | 0.9177   | 0.5499        | 0.6569     | 0.5987 | 0.0               | 0.0            | 0.0        | 0.8922         | 0.9030      | 0.8976  | 0.2459            | 0.3333         | 0.2830     | 0.5               | 0.1481         | 0.2286     | 0.7219          | 0.7774       | 0.7486   | 0.0                 | 0.0              | 0.0          | 0.9518           | 0.9576        | 0.9547    | 0.3061              | 0.3333           | 0.3191       | 0.5                 | 0.16             | 0.2424       | 0.5759          | 0.6818       | 0.6244   | 0.0                 | 0.0              | 0.0          | 0.9146           | 0.9091        | 0.9119    | 0.3333              | 0.4737           | 0.3913       | 0.0                 | 0.0              | 0.0          | 0.4192       | 0.6923          |
| 0.2709        | 5.0   | 635  | 0.2856          | 0.5714    | 0.6542 | 0.6100 | 0.9180   | 0.5455        | 0.6606     | 0.5975 | 0.075             | 0.1579         | 0.1017     | 0.9085         | 0.9030      | 0.9058  | 0.1667            | 0.1333         | 0.1481     | 0.3529            | 0.2222         | 0.2727     | 0.7284          | 0.7774       | 0.7521   | 0.1429              | 0.2105           | 0.1702       | 0.9693           | 0.9576        | 0.9634    | 0.2917              | 0.1556           | 0.2029       | 0.5                 | 0.24             | 0.3243       | 0.5616          | 0.6905       | 0.6194   | 0.1176              | 0.25             | 0.1600       | 0.9202           | 0.9091        | 0.9146    | 0.25                | 0.1579           | 0.1935       | 0.5                 | 0.15             | 0.2308       | 0.4531       | 0.6930          |
| 0.2709        | 6.0   | 762  | 0.3053          | 0.5488    | 0.6529 | 0.5964 | 0.9140   | 0.5331        | 0.6642     | 0.5915 | 0.0               | 0.0            | 0.0        | 0.8976         | 0.9030      | 0.9003  | 0.0962            | 0.1111         | 0.1031     | 0.4667            | 0.2593         | 0.3333     | 0.7073          | 0.8023       | 0.7518   | 0.0                 | 0.0              | 0.0          | 0.9636           | 0.9636        | 0.9636    | 0.2927              | 0.2667           | 0.2791       | 0.7273              | 0.32             | 0.4444       | 0.5554          | 0.6732       | 0.6086   | 0.1053              | 0.25             | 0.1481       | 0.9030           | 0.9030        | 0.9030    | 0.2222              | 0.1579           | 0.1846       | 0.6                 | 0.15             | 0.24         | 0.4523       | 0.6902          |
| 0.2709        | 7.0   | 889  | 0.3162          | 0.5816    | 0.6717 | 0.6234 | 0.9200   | 0.5605        | 0.6716     | 0.6110 | 0.0               | 0.0            | 0.0        | 0.9102         | 0.9212      | 0.9157  | 0.1607            | 0.2            | 0.1782     | 0.5               | 0.4074         | 0.4490     | 0.7207          | 0.8023       | 0.7593   | 0.1667              | 0.0526           | 0.08         | 0.9639           | 0.9697        | 0.9668    | 0.3261              | 0.3333           | 0.3297       | 0.6875              | 0.44             | 0.5366       | 0.5769          | 0.6818       | 0.6250   | 0.0385              | 0.0625           | 0.0476       | 0.9268           | 0.9212        | 0.9240    | 0.2                 | 0.2105           | 0.2051       | 0.4545              | 0.25             | 0.3226       | 0.4797       | 0.7054          |
| 0.0894        | 8.0   | 1016 | 0.3347          | 0.5935    | 0.6891 | 0.6378 | 0.9181   | 0.5595        | 0.6899     | 0.6179 | 0.0               | 0.0            | 0.0        | 0.8876         | 0.9091      | 0.8982  | 0.2712            | 0.3556         | 0.3077     | 0.5556            | 0.3704         | 0.4444     | 0.7167          | 0.8157       | 0.7630   | 0.0                 | 0.0              | 0.0          | 0.9581           | 0.9697        | 0.9639    | 0.3404              | 0.3556           | 0.3478       | 0.8462              | 0.44             | 0.5789       | 0.5786          | 0.7013       | 0.6341   | 0.0                 | 0.0              | 0.0          | 0.8929           | 0.9091        | 0.9009    | 0.3265              | 0.4211           | 0.3678       | 0.4444              | 0.2              | 0.2759       | 0.4832       | 0.7099          |
| 0.0894        | 9.0   | 1143 | 0.3441          | 0.5813    | 0.6742 | 0.6243 | 0.9194   | 0.5549        | 0.6771     | 0.6099 | 0.0               | 0.0            | 0.0        | 0.8817         | 0.9030      | 0.8922  | 0.2182            | 0.2667         | 0.2400     | 0.5263            | 0.3704         | 0.4348     | 0.7197          | 0.8081       | 0.7613   | 0.0                 | 0.0              | 0.0          | 0.9524           | 0.9697        | 0.9610    | 0.3478              | 0.3556           | 0.3516       | 0.8462              | 0.44             | 0.5789       | 0.5727          | 0.6905       | 0.6261   | 0.0                 | 0.0              | 0.0          | 0.8976           | 0.9030        | 0.9003    | 0.2683              | 0.2895           | 0.2785       | 0.4                 | 0.2              | 0.2667       | 0.4724       | 0.7041          |
| 0.0894        | 10.0  | 1270 | 0.3476          | 0.5870    | 0.6866 | 0.6329 | 0.9193   | 0.5614        | 0.6881     | 0.6183 | 0.0               | 0.0            | 0.0        | 0.8988         | 0.9152      | 0.9069  | 0.2295            | 0.3111         | 0.2642     | 0.4762            | 0.3704         | 0.4167     | 0.7133          | 0.8119       | 0.7594   | 0.0                 | 0.0              | 0.0          | 0.9639           | 0.9697        | 0.9668    | 0.3469              | 0.3778           | 0.3617       | 0.7857              | 0.44             | 0.5641       | 0.5799          | 0.6991       | 0.6340   | 0.0                 | 0.0              | 0.0          | 0.9042           | 0.9152        | 0.9096    | 0.2979              | 0.3684           | 0.3294       | 0.3333              | 0.2              | 0.25         | 0.4775       | 0.7087          |


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