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# electra-base-discriminator-finetuned-ner-cadec-no-iob

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: 0.3907
- Precision: 0.6459
- Recall: 0.6715
- F1: 0.6585
- Accuracy: 0.9355
- Adr Precision: 0.5961
- Adr Recall: 0.6330
- Adr F1: 0.614
- Disease Precision: 0.4615
- Disease Recall: 0.375
- Disease F1: 0.4138
- Drug Precision: 0.9022
- Drug Recall: 0.9222
- Drug F1: 0.9121
- Finding Precision: 0.2571
- Finding Recall: 0.2812
- Finding F1: 0.2687
- Symptom Precision: 0.5357
- Symptom Recall: 0.5172
- Symptom F1: 0.5263
- Macro Avg F1: 0.5470
- Weighted Avg F1: 0.6584

## 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: 40

### 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 | Macro Avg F1 | Weighted Avg F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|:------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------:|:-------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:------------:|:---------------:|
| No log        | 1.0   | 125  | 0.2178          | 0.5120    | 0.5646 | 0.5370 | 0.9209   | 0.4311        | 0.5608     | 0.4875 | 0.1               | 0.0312         | 0.0476     | 0.8158         | 0.8611      | 0.8378  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.2746       | 0.5129          |
| No log        | 2.0   | 250  | 0.1864          | 0.5799    | 0.6227 | 0.6005 | 0.9296   | 0.5017        | 0.6        | 0.5465 | 0.4146            | 0.5312         | 0.4658     | 0.9011         | 0.9111      | 0.9061  | 0.0               | 0.0            | 0.0        | 0.0               | 0.0            | 0.0        | 0.3837       | 0.5845          |
| No log        | 3.0   | 375  | 0.1845          | 0.5894    | 0.6306 | 0.6093 | 0.9310   | 0.5520        | 0.6021     | 0.5759 | 0.2353            | 0.375          | 0.2892     | 0.9016         | 0.9167      | 0.9091  | 0.0857            | 0.0938         | 0.0896     | 0.4615            | 0.2069         | 0.2857     | 0.4299       | 0.6113          |
| 0.2159        | 4.0   | 500  | 0.1968          | 0.6002    | 0.6359 | 0.6176 | 0.9318   | 0.5570        | 0.6041     | 0.5796 | 0.0667            | 0.0312         | 0.0426     | 0.9121         | 0.9222      | 0.9171  | 0.1967            | 0.375          | 0.2581     | 0.5263            | 0.3448         | 0.4167     | 0.4428       | 0.6173          |
| 0.2159        | 5.0   | 625  | 0.2026          | 0.6357    | 0.6583 | 0.6468 | 0.9338   | 0.5817        | 0.6165     | 0.5986 | 0.52              | 0.4062         | 0.4561     | 0.9071         | 0.9222      | 0.9146  | 0.1951            | 0.25           | 0.2192     | 0.5909            | 0.4483         | 0.5098     | 0.5397       | 0.6482          |
| 0.2159        | 6.0   | 750  | 0.2142          | 0.6055    | 0.6359 | 0.6203 | 0.9319   | 0.5697        | 0.5814     | 0.5755 | 0.375             | 0.4688         | 0.4167     | 0.9066         | 0.9167      | 0.9116  | 0.1163            | 0.1562         | 0.1333     | 0.4167            | 0.5172         | 0.4615     | 0.4997       | 0.6256          |
| 0.2159        | 7.0   | 875  | 0.2283          | 0.6420    | 0.6649 | 0.6533 | 0.9328   | 0.5867        | 0.6206     | 0.6032 | 0.5               | 0.3125         | 0.3846     | 0.9076         | 0.9278      | 0.9176  | 0.2444            | 0.3438         | 0.2857     | 0.6522            | 0.5172         | 0.5769     | 0.5536       | 0.6542          |
| 0.0651        | 8.0   | 1000 | 0.2430          | 0.6103    | 0.6570 | 0.6328 | 0.9312   | 0.5632        | 0.6062     | 0.5839 | 0.5625            | 0.2812         | 0.375      | 0.9121         | 0.9222      | 0.9171  | 0.2241            | 0.4062         | 0.2889     | 0.4211            | 0.5517         | 0.4776     | 0.5285       | 0.6377          |
| 0.0651        | 9.0   | 1125 | 0.2367          | 0.6308    | 0.6583 | 0.6443 | 0.9338   | 0.5800        | 0.6206     | 0.5996 | 0.48              | 0.375          | 0.4211     | 0.8811         | 0.9056      | 0.8932  | 0.2286            | 0.25           | 0.2388     | 0.5556            | 0.5172         | 0.5357     | 0.5377       | 0.6441          |
| 0.0651        | 10.0  | 1250 | 0.2694          | 0.6241    | 0.6570 | 0.6401 | 0.9294   | 0.5639        | 0.6186     | 0.5900 | 0.4286            | 0.2812         | 0.3396     | 0.9171         | 0.9222      | 0.9197  | 0.2222            | 0.3125         | 0.2597     | 0.6842            | 0.4483         | 0.5417     | 0.5301       | 0.6419          |
| 0.0651        | 11.0  | 1375 | 0.2731          | 0.61      | 0.6438 | 0.6264 | 0.9325   | 0.5626        | 0.6021     | 0.5817 | 0.4286            | 0.375          | 0.4000     | 0.8511         | 0.8889      | 0.8696  | 0.2812            | 0.2812         | 0.2812     | 0.4545            | 0.5172         | 0.4839     | 0.5233       | 0.6259          |
| 0.0265        | 12.0  | 1500 | 0.2842          | 0.6221    | 0.6451 | 0.6334 | 0.9323   | 0.5697        | 0.5979     | 0.5835 | 0.3929            | 0.3438         | 0.3667     | 0.9027         | 0.9278      | 0.9151  | 0.2121            | 0.2188         | 0.2154     | 0.4516            | 0.4828         | 0.4667     | 0.5095       | 0.6331          |
| 0.0265        | 13.0  | 1625 | 0.2861          | 0.6438    | 0.6675 | 0.6554 | 0.9348   | 0.5802        | 0.6268     | 0.6026 | 0.5               | 0.4375         | 0.4667     | 0.9278         | 0.9278      | 0.9278  | 0.3               | 0.2812         | 0.2903     | 0.5               | 0.4138         | 0.4528     | 0.5480       | 0.6552          |
| 0.0265        | 14.0  | 1750 | 0.3202          | 0.6413    | 0.6557 | 0.6484 | 0.9323   | 0.5742        | 0.6144     | 0.5936 | 0.5263            | 0.3125         | 0.3922     | 0.9071         | 0.9222      | 0.9146  | 0.2647            | 0.2812         | 0.2727     | 0.7               | 0.4828         | 0.5714     | 0.5489       | 0.6469          |
| 0.0265        | 15.0  | 1875 | 0.3118          | 0.6284    | 0.6491 | 0.6385 | 0.9336   | 0.5731        | 0.6062     | 0.5892 | 0.4348            | 0.3125         | 0.3636     | 0.9066         | 0.9167      | 0.9116  | 0.25              | 0.3125         | 0.2778     | 0.52              | 0.4483         | 0.4815     | 0.5247       | 0.6390          |
| 0.0115        | 16.0  | 2000 | 0.3144          | 0.6293    | 0.6583 | 0.6435 | 0.9335   | 0.5747        | 0.6268     | 0.5996 | 0.3846            | 0.3125         | 0.3448     | 0.9061         | 0.9111      | 0.9086  | 0.2286            | 0.25           | 0.2388     | 0.5909            | 0.4483         | 0.5098     | 0.5203       | 0.6436          |
| 0.0115        | 17.0  | 2125 | 0.3235          | 0.6411    | 0.6623 | 0.6515 | 0.9346   | 0.5918        | 0.6247     | 0.6078 | 0.4               | 0.375          | 0.3871     | 0.9171         | 0.9222      | 0.9197  | 0.2121            | 0.2188         | 0.2154     | 0.5185            | 0.4828         | 0.5        | 0.5260       | 0.6519          |
| 0.0115        | 18.0  | 2250 | 0.3258          | 0.6230    | 0.6583 | 0.6402 | 0.9344   | 0.5948        | 0.6144     | 0.6045 | 0.3429            | 0.375          | 0.3582     | 0.8913         | 0.9111      | 0.9011  | 0.1957            | 0.2812         | 0.2308     | 0.4571            | 0.5517         | 0.5        | 0.5189       | 0.6447          |
| 0.0115        | 19.0  | 2375 | 0.3347          | 0.6312    | 0.6728 | 0.6513 | 0.9361   | 0.5794        | 0.6392     | 0.6078 | 0.4348            | 0.3125         | 0.3636     | 0.9022         | 0.9222      | 0.9121  | 0.2564            | 0.3125         | 0.2817     | 0.5185            | 0.4828         | 0.5        | 0.5331       | 0.6519          |
| 0.0076        | 20.0  | 2500 | 0.3334          | 0.6508    | 0.6662 | 0.6584 | 0.9328   | 0.6031        | 0.6330     | 0.6177 | 0.375             | 0.375          | 0.375      | 0.9231         | 0.9333      | 0.9282  | 0.1765            | 0.1875         | 0.1818     | 0.6316            | 0.4138         | 0.5        | 0.5205       | 0.6583          |
| 0.0076        | 21.0  | 2625 | 0.3426          | 0.6385    | 0.6781 | 0.6577 | 0.9344   | 0.5943        | 0.6495     | 0.6207 | 0.4231            | 0.3438         | 0.3793     | 0.9071         | 0.9222      | 0.9146  | 0.1765            | 0.1875         | 0.1818     | 0.5               | 0.5517         | 0.5246     | 0.5242       | 0.6581          |
| 0.0076        | 22.0  | 2750 | 0.3431          | 0.6269    | 0.6649 | 0.6453 | 0.9344   | 0.5862        | 0.6309     | 0.6077 | 0.3793            | 0.3438         | 0.3607     | 0.9071         | 0.9222      | 0.9146  | 0.1707            | 0.2188         | 0.1918     | 0.4828            | 0.4828         | 0.4828     | 0.5115       | 0.6478          |
| 0.0076        | 23.0  | 2875 | 0.3374          | 0.6410    | 0.6689 | 0.6546 | 0.9348   | 0.5913        | 0.6412     | 0.6152 | 0.3913            | 0.2812         | 0.3273     | 0.9180         | 0.9333      | 0.9256  | 0.2368            | 0.2812         | 0.2571     | 0.4762            | 0.3448         | 0.4000     | 0.5051       | 0.6534          |
| 0.0049        | 24.0  | 3000 | 0.3484          | 0.6338    | 0.6530 | 0.6433 | 0.9352   | 0.5819        | 0.6082     | 0.5948 | 0.4               | 0.375          | 0.3871     | 0.9126         | 0.9278      | 0.9201  | 0.2258            | 0.2188         | 0.2222     | 0.4667            | 0.4828         | 0.4746     | 0.5198       | 0.6429          |
| 0.0049        | 25.0  | 3125 | 0.3441          | 0.6444    | 0.6741 | 0.6589 | 0.9362   | 0.6015        | 0.6412     | 0.6208 | 0.4194            | 0.4062         | 0.4127     | 0.9076         | 0.9278      | 0.9176  | 0.1935            | 0.1875         | 0.1905     | 0.4667            | 0.4828         | 0.4746     | 0.5232       | 0.6587          |
| 0.0049        | 26.0  | 3250 | 0.3573          | 0.6330    | 0.6689 | 0.6504 | 0.9347   | 0.5802        | 0.6268     | 0.6026 | 0.4138            | 0.375          | 0.3934     | 0.9235         | 0.9389      | 0.9311  | 0.2286            | 0.25           | 0.2388     | 0.4667            | 0.4828         | 0.4746     | 0.5281       | 0.6515          |
| 0.0049        | 27.0  | 3375 | 0.3589          | 0.6477    | 0.6596 | 0.6536 | 0.9336   | 0.5909        | 0.6165     | 0.6034 | 0.48              | 0.375          | 0.4211     | 0.9126         | 0.9278      | 0.9201  | 0.25              | 0.2812         | 0.2647     | 0.5909            | 0.4483         | 0.5098     | 0.5438       | 0.6531          |
| 0.0037        | 28.0  | 3500 | 0.3629          | 0.6307    | 0.6715 | 0.6505 | 0.9354   | 0.5900        | 0.6351     | 0.6117 | 0.4444            | 0.375          | 0.4068     | 0.9016         | 0.9167      | 0.9091  | 0.2326            | 0.3125         | 0.2667     | 0.4375            | 0.4828         | 0.4590     | 0.5307       | 0.6533          |
| 0.0037        | 29.0  | 3625 | 0.3694          | 0.6490    | 0.6781 | 0.6632 | 0.9358   | 0.6035        | 0.6433     | 0.6228 | 0.4286            | 0.375          | 0.4000     | 0.9071         | 0.9222      | 0.9146  | 0.2105            | 0.25           | 0.2286     | 0.6154            | 0.5517         | 0.5818     | 0.5495       | 0.6644          |
| 0.0037        | 30.0  | 3750 | 0.3779          | 0.6456    | 0.6728 | 0.6589 | 0.9350   | 0.5946        | 0.6351     | 0.6142 | 0.5               | 0.375          | 0.4286     | 0.9071         | 0.9222      | 0.9146  | 0.2647            | 0.2812         | 0.2727     | 0.4839            | 0.5172         | 0.5000     | 0.5460       | 0.6589          |
| 0.0037        | 31.0  | 3875 | 0.3776          | 0.6465    | 0.6636 | 0.6549 | 0.9360   | 0.5992        | 0.6227     | 0.6107 | 0.4615            | 0.375          | 0.4138     | 0.9022         | 0.9222      | 0.9121  | 0.2424            | 0.25           | 0.2462     | 0.4839            | 0.5172         | 0.5000     | 0.5366       | 0.6543          |
| 0.0027        | 32.0  | 4000 | 0.3775          | 0.6429    | 0.6675 | 0.6550 | 0.9355   | 0.5984        | 0.6268     | 0.6123 | 0.4444            | 0.375          | 0.4068     | 0.9022         | 0.9222      | 0.9121  | 0.2368            | 0.2812         | 0.2571     | 0.5               | 0.5172         | 0.5085     | 0.5394       | 0.6558          |
| 0.0027        | 33.0  | 4125 | 0.3784          | 0.6378    | 0.6715 | 0.6542 | 0.9363   | 0.5881        | 0.6330     | 0.6097 | 0.4783            | 0.3438         | 0.4        | 0.9022         | 0.9222      | 0.9121  | 0.2381            | 0.3125         | 0.2703     | 0.5556            | 0.5172         | 0.5357     | 0.5456       | 0.6555          |
| 0.0027        | 34.0  | 4250 | 0.3824          | 0.6332    | 0.6741 | 0.6530 | 0.9356   | 0.5830        | 0.6371     | 0.6089 | 0.4286            | 0.375          | 0.4000     | 0.9022         | 0.9222      | 0.9121  | 0.2432            | 0.2812         | 0.2609     | 0.5357            | 0.5172         | 0.5263     | 0.5416       | 0.6542          |
| 0.0027        | 35.0  | 4375 | 0.3825          | 0.6415    | 0.6728 | 0.6568 | 0.9358   | 0.5954        | 0.6371     | 0.6155 | 0.4444            | 0.375          | 0.4068     | 0.9022         | 0.9222      | 0.9121  | 0.225             | 0.2812         | 0.25       | 0.56              | 0.4828         | 0.5185     | 0.5406       | 0.6580          |
| 0.0018        | 36.0  | 4500 | 0.3841          | 0.6390    | 0.6794 | 0.6586 | 0.9364   | 0.5928        | 0.6454     | 0.6180 | 0.4444            | 0.375          | 0.4068     | 0.9022         | 0.9222      | 0.9121  | 0.2368            | 0.2812         | 0.2571     | 0.5172            | 0.5172         | 0.5172     | 0.5422       | 0.6598          |
| 0.0018        | 37.0  | 4625 | 0.3892          | 0.6477    | 0.6741 | 0.6606 | 0.9361   | 0.6008        | 0.6392     | 0.6194 | 0.4286            | 0.375          | 0.4000     | 0.9022         | 0.9222      | 0.9121  | 0.2571            | 0.2812         | 0.2687     | 0.5385            | 0.4828         | 0.5091     | 0.5418       | 0.6606          |
| 0.0018        | 38.0  | 4750 | 0.3893          | 0.6480    | 0.6702 | 0.6589 | 0.9363   | 0.5988        | 0.6309     | 0.6145 | 0.4444            | 0.375          | 0.4068     | 0.9022         | 0.9222      | 0.9121  | 0.25              | 0.2812         | 0.2647     | 0.5769            | 0.5172         | 0.5455     | 0.5487       | 0.6590          |
| 0.0018        | 39.0  | 4875 | 0.3911          | 0.6422    | 0.6702 | 0.6559 | 0.9354   | 0.5907        | 0.6309     | 0.6102 | 0.4615            | 0.375          | 0.4138     | 0.9022         | 0.9222      | 0.9121  | 0.2571            | 0.2812         | 0.2687     | 0.5357            | 0.5172         | 0.5263     | 0.5462       | 0.6559          |
| 0.0016        | 40.0  | 5000 | 0.3907          | 0.6459    | 0.6715 | 0.6585 | 0.9355   | 0.5961        | 0.6330     | 0.614  | 0.4615            | 0.375          | 0.4138     | 0.9022         | 0.9222      | 0.9121  | 0.2571            | 0.2812         | 0.2687     | 0.5357            | 0.5172         | 0.5263     | 0.5470       | 0.6584          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- 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-discriminator-finetuned-ner-cadec-no-iob", "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