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# albert-base-v2-finetuned-ner-cadec

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3782
- Precision: 0.6044
- Recall: 0.6542
- F1: 0.6283
- Accuracy: 0.9197
- Adr Precision: 0.5756
- Adr Recall: 0.6495
- Adr F1: 0.6103
- Disease Precision: 0.1923
- Disease Recall: 0.2632
- Disease F1: 0.2222
- Drug Precision: 0.9259
- Drug Recall: 0.9091
- Drug F1: 0.9174
- Finding Precision: 0.1667
- Finding Recall: 0.2
- Finding F1: 0.1818
- Symptom Precision: 0.6
- Symptom Recall: 0.2222
- Symptom F1: 0.3243
- B-adr Precision: 0.7331
- B-adr Recall: 0.7908
- B-adr F1: 0.7608
- B-disease Precision: 0.2778
- B-disease Recall: 0.2632
- B-disease F1: 0.2703
- B-drug Precision: 0.9630
- B-drug Recall: 0.9455
- B-drug F1: 0.9541
- B-finding Precision: 0.2391
- B-finding Recall: 0.2444
- B-finding F1: 0.2418
- B-symptom Precision: 0.75
- B-symptom Recall: 0.24
- B-symptom F1: 0.3636
- I-adr Precision: 0.5746
- I-adr Recall: 0.6524
- I-adr F1: 0.6110
- I-disease Precision: 0.2222
- I-disease Recall: 0.3077
- I-disease F1: 0.2581
- I-drug Precision: 0.9259
- I-drug Recall: 0.9202
- I-drug F1: 0.9231
- I-finding Precision: 0.1842
- I-finding Recall: 0.2188
- I-finding F1: 0.2000
- I-symptom Precision: 0.25
- I-symptom Recall: 0.0476
- I-symptom F1: 0.08
- Macro Avg F1: 0.4663
- Weighted Avg F1: 0.6990

## 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  | 0.2569          | 0.5268    | 0.6142 | 0.5671 | 0.9148   | 0.4666        | 0.6275     | 0.5352 | 0.0               | 0.0            | 0.0        | 0.8471         | 0.8727      | 0.8597  | 0.1935            | 0.1333         | 0.1579     | 0.0               | 0.0            | 0.0        | 0.6758          | 0.7601       | 0.7154   | 0.0                 | 0.0              | 0.0          | 0.9157           | 0.9212        | 0.9184    | 0.3                 | 0.0667           | 0.1091       | 0.0                 | 0.0              | 0.0          | 0.4694          | 0.6411       | 0.5420   | 0.0                 | 0.0              | 0.0          | 0.8683           | 0.8896        | 0.8788    | 0.2                 | 0.1875           | 0.1935       | 0.0                 | 0.0              | 0.0          | 0.3357       | 0.6349          |
| No log        | 2.0   | 254  | 0.2418          | 0.5393    | 0.5993 | 0.5677 | 0.9159   | 0.5219        | 0.6110     | 0.5630 | 0.0645            | 0.1053         | 0.0800     | 0.8438         | 0.8182      | 0.8308  | 0.1379            | 0.1778         | 0.1553     | 0.6667            | 0.0741         | 0.1333     | 0.7396          | 0.7524       | 0.7460   | 0.1                 | 0.1053           | 0.1026       | 0.9618           | 0.9152        | 0.9379    | 0.2093              | 0.2              | 0.2045       | 0.6667              | 0.08             | 0.1429       | 0.5226          | 0.6275       | 0.5703   | 0.0526              | 0.0769           | 0.0625       | 0.8491           | 0.8282        | 0.8385    | 0.25                | 0.3125           | 0.2778       | 0.0                 | 0.0              | 0.0          | 0.3883       | 0.6615          |
| No log        | 3.0   | 381  | 0.2577          | 0.6019    | 0.6380 | 0.6194 | 0.9226   | 0.5747        | 0.6422     | 0.6066 | 0.0909            | 0.1579         | 0.1154     | 0.9036         | 0.9091      | 0.9063  | 0.1579            | 0.1333         | 0.1446     | 0.6667            | 0.0741         | 0.1333     | 0.7598          | 0.7774       | 0.7685   | 0.2593              | 0.3684           | 0.3043       | 0.9455           | 0.9455        | 0.9455    | 0.2308              | 0.1333           | 0.1690       | 0.6667              | 0.08             | 0.1429       | 0.5881          | 0.6479       | 0.6165   | 0.0769              | 0.0769           | 0.0769       | 0.9091           | 0.9202        | 0.9146    | 0.2581              | 0.25             | 0.2540       | 0.0                 | 0.0              | 0.0          | 0.4192       | 0.6943          |
| 0.2396        | 4.0   | 508  | 0.2655          | 0.6073    | 0.6429 | 0.6246 | 0.9200   | 0.5840        | 0.6440     | 0.6126 | 0.0               | 0.0            | 0.0        | 0.9012         | 0.8848      | 0.8930  | 0.2222            | 0.3111         | 0.2593     | 0.6667            | 0.1481         | 0.2424     | 0.7678          | 0.7678       | 0.7678   | 0.0                 | 0.0              | 0.0          | 0.9689           | 0.9455        | 0.9571    | 0.2745              | 0.3111           | 0.2917       | 1.0                 | 0.24             | 0.3871       | 0.5732          | 0.6185       | 0.5950   | 0.1                 | 0.0769           | 0.0870       | 0.9068           | 0.8957        | 0.9012    | 0.2766              | 0.4062           | 0.3291       | 0.0                 | 0.0              | 0.0          | 0.4316       | 0.6931          |
| 0.2396        | 5.0   | 635  | 0.2875          | 0.5769    | 0.6367 | 0.6053 | 0.9175   | 0.5669        | 0.6532     | 0.6070 | 0.1053            | 0.2105         | 0.1404     | 0.8598         | 0.8545      | 0.8571  | 0.1087            | 0.1111         | 0.1099     | 0.5               | 0.1481         | 0.2286     | 0.7319          | 0.7965       | 0.7629   | 0.2188              | 0.3684           | 0.2745       | 0.9627           | 0.9394        | 0.9509    | 0.1852              | 0.1111           | 0.1389       | 0.5714              | 0.16             | 0.25         | 0.5686          | 0.6546       | 0.6086   | 0.1053              | 0.1538           | 0.125        | 0.8650           | 0.8650        | 0.8650    | 0.2105              | 0.25             | 0.2286       | 0.0                 | 0.0              | 0.0          | 0.4204       | 0.6853          |
| 0.2396        | 6.0   | 762  | 0.3081          | 0.6063    | 0.6442 | 0.6247 | 0.9188   | 0.5809        | 0.6459     | 0.6116 | 0.1923            | 0.2632         | 0.2222     | 0.8841         | 0.8788      | 0.8815  | 0.2               | 0.2222         | 0.2105     | 0.8               | 0.1481         | 0.25       | 0.7409          | 0.7793       | 0.7596   | 0.2381              | 0.2632           | 0.25         | 0.9571           | 0.9455        | 0.9512    | 0.2381              | 0.2222           | 0.2299       | 0.8                 | 0.16             | 0.2667       | 0.5773          | 0.6659       | 0.6184   | 0.25                | 0.3077           | 0.2759       | 0.8896           | 0.8896        | 0.8896    | 0.2571              | 0.2812           | 0.2687       | 0.0                 | 0.0              | 0.0          | 0.4510       | 0.6950          |
| 0.2396        | 7.0   | 889  | 0.3203          | 0.6147    | 0.6692 | 0.6408 | 0.9196   | 0.5903        | 0.6716     | 0.6283 | 0.15              | 0.1579         | 0.1538     | 0.8976         | 0.9030      | 0.9003  | 0.2182            | 0.2667         | 0.2400     | 0.5455            | 0.2222         | 0.3158     | 0.7442          | 0.7985       | 0.7704   | 0.2857              | 0.2105           | 0.2424       | 0.9398           | 0.9455        | 0.9426    | 0.2667              | 0.2667           | 0.2667       | 0.7778              | 0.28             | 0.4118       | 0.5783          | 0.6501       | 0.6121   | 0.1765              | 0.2308           | 0.2000       | 0.9085           | 0.9141        | 0.9113    | 0.2222              | 0.25             | 0.2353       | 0.6                 | 0.1429           | 0.2308       | 0.4823       | 0.7039          |
| 0.0784        | 8.0   | 1016 | 0.3548          | 0.5995    | 0.6429 | 0.6205 | 0.9183   | 0.5783        | 0.6367     | 0.6061 | 0.15              | 0.1579         | 0.1538     | 0.8916         | 0.8970      | 0.8943  | 0.1875            | 0.2667         | 0.2202     | 0.5556            | 0.1852         | 0.2778     | 0.7454          | 0.7754       | 0.7601   | 0.2857              | 0.2105           | 0.2424       | 0.9455           | 0.9455        | 0.9455    | 0.2545              | 0.3111           | 0.2800       | 0.625               | 0.2              | 0.3030       | 0.5683          | 0.6388       | 0.6015   | 0.2                 | 0.2308           | 0.2143       | 0.8970           | 0.9080        | 0.9024    | 0.1957              | 0.2812           | 0.2308       | 0.3333              | 0.0476           | 0.0833       | 0.4563       | 0.6927          |
| 0.0784        | 9.0   | 1143 | 0.3721          | 0.6101    | 0.6604 | 0.6343 | 0.9209   | 0.5812        | 0.6569     | 0.6167 | 0.25              | 0.2632         | 0.2564     | 0.9202         | 0.9091      | 0.9146  | 0.1964            | 0.2444         | 0.2178     | 0.4167            | 0.1852         | 0.2564     | 0.7300          | 0.7889       | 0.7583   | 0.3125              | 0.2632           | 0.2857       | 0.9630           | 0.9455        | 0.9541    | 0.2340              | 0.2444           | 0.2391       | 0.625               | 0.2              | 0.3030       | 0.5828          | 0.6591       | 0.6186   | 0.2857              | 0.3077           | 0.2963       | 0.9259           | 0.9202        | 0.9231    | 0.2432              | 0.2812           | 0.2609       | 0.3333              | 0.0952           | 0.1481       | 0.4787       | 0.7022          |
| 0.0784        | 10.0  | 1270 | 0.3782          | 0.6044    | 0.6542 | 0.6283 | 0.9197   | 0.5756        | 0.6495     | 0.6103 | 0.1923            | 0.2632         | 0.2222     | 0.9259         | 0.9091      | 0.9174  | 0.1667            | 0.2            | 0.1818     | 0.6               | 0.2222         | 0.3243     | 0.7331          | 0.7908       | 0.7608   | 0.2778              | 0.2632           | 0.2703       | 0.9630           | 0.9455        | 0.9541    | 0.2391              | 0.2444           | 0.2418       | 0.75                | 0.24             | 0.3636       | 0.5746          | 0.6524       | 0.6110   | 0.2222              | 0.3077           | 0.2581       | 0.9259           | 0.9202        | 0.9231    | 0.1842              | 0.2188           | 0.2000       | 0.25                | 0.0476           | 0.08         | 0.4663       | 0.6990          |


### 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": "albert-base-v2", "model-index": [{"name": "albert-base-v2-finetuned-ner-cadec", "results": []}]}
transformers tensorboard safetensors albert token-classification generated_from_trainer base_model:albert-base-v2 license:apache-2.0 autotrain_compatible endpoints_compatible region:us