
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta-base-finetuned-ner-cadec-no-iob

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4142
- Precision: 0.6452
- Recall: 0.6860
- F1: 0.6650
- Accuracy: 0.9380
- Adr Precision: 0.5911
- Adr Recall: 0.6557
- Adr F1: 0.6217
- Disease Precision: 0.4138
- Disease Recall: 0.375
- Disease F1: 0.3934
- Drug Precision: 0.8962
- Drug Recall: 0.9111
- Drug F1: 0.9036
- Finding Precision: 0.375
- Finding Recall: 0.375
- Finding F1: 0.375
- Symptom Precision: 0.5833
- Symptom Recall: 0.4828
- Symptom F1: 0.5283
- Macro Avg F1: 0.5644
- Weighted Avg F1: 0.6650

## 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: 35

### 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  | 0.2142          | 0.5325    | 0.6055 | 0.5667 | 0.9194   | 0.4548        | 0.5918     | 0.5143 | 0.4186            | 0.5625         | 0.48       | 0.8398         | 0.8444      | 0.8421  | 0.2857            | 0.0625         | 0.1026     | 0.0               | 0.0            | 0.0        | 0.3878       | 0.5537          |
| No log        | 2.0   | 250  | 0.1798          | 0.6083    | 0.6557 | 0.6311 | 0.9339   | 0.5276        | 0.6309     | 0.5746 | 0.6842            | 0.4062         | 0.5098     | 0.8950         | 0.9         | 0.8975  | 0.32              | 0.25           | 0.2807     | 0.6667            | 0.2759         | 0.3902     | 0.5306       | 0.6291          |
| No log        | 3.0   | 375  | 0.1910          | 0.5748    | 0.6029 | 0.5885 | 0.9282   | 0.5191        | 0.5320     | 0.5255 | 0.6               | 0.375          | 0.4615     | 0.8820         | 0.8722      | 0.8771  | 0.2927            | 0.375          | 0.3288     | 0.3051            | 0.6207         | 0.4091     | 0.5204       | 0.5935          |
| 0.1902        | 4.0   | 500  | 0.2013          | 0.5995    | 0.6398 | 0.6190 | 0.9311   | 0.5460        | 0.6        | 0.5717 | 0.25              | 0.0938         | 0.1364     | 0.8840         | 0.8889      | 0.8864  | 0.2632            | 0.4688         | 0.3371     | 0.6154            | 0.5517         | 0.5818     | 0.5027       | 0.6185          |
| 0.1902        | 5.0   | 625  | 0.2113          | 0.6161    | 0.6649 | 0.6396 | 0.9335   | 0.5515        | 0.6289     | 0.5877 | 0.5556            | 0.4688         | 0.5085     | 0.8852         | 0.9         | 0.8926  | 0.2857            | 0.25           | 0.2667     | 0.5185            | 0.4828         | 0.5        | 0.5511       | 0.6398          |
| 0.1902        | 6.0   | 750  | 0.1955          | 0.6223    | 0.6544 | 0.6379 | 0.9341   | 0.5541        | 0.6021     | 0.5771 | 0.5833            | 0.4375         | 0.5        | 0.8956         | 0.9056      | 0.9006  | 0.2857            | 0.375          | 0.3243     | 0.6818            | 0.5172         | 0.5882     | 0.5780       | 0.6404          |
| 0.1902        | 7.0   | 875  | 0.2226          | 0.6252    | 0.6491 | 0.6369 | 0.9343   | 0.5671        | 0.6186     | 0.5917 | 0.5556            | 0.1562         | 0.2439     | 0.8983         | 0.8833      | 0.8908  | 0.3061            | 0.4688         | 0.3704     | 0.5652            | 0.4483         | 0.5000     | 0.5193       | 0.6352          |
| 0.0648        | 8.0   | 1000 | 0.2345          | 0.6229    | 0.6755 | 0.6481 | 0.9363   | 0.5773        | 0.6392     | 0.6067 | 0.4138            | 0.375          | 0.3934     | 0.875          | 0.8944      | 0.8846  | 0.2973            | 0.3438         | 0.3188     | 0.5143            | 0.6207         | 0.5625     | 0.5532       | 0.6498          |
| 0.0648        | 9.0   | 1125 | 0.2316          | 0.6322    | 0.6689 | 0.65   | 0.9368   | 0.5851        | 0.6309     | 0.6071 | 0.5               | 0.3125         | 0.3846     | 0.8811         | 0.9056      | 0.8932  | 0.2766            | 0.4062         | 0.3291     | 0.5556            | 0.5172         | 0.5357     | 0.5499       | 0.6512          |
| 0.0648        | 10.0  | 1250 | 0.2944          | 0.6204    | 0.6491 | 0.6344 | 0.9320   | 0.5551        | 0.6021     | 0.5776 | 0.5789            | 0.3438         | 0.4314     | 0.8913         | 0.9111      | 0.9011  | 0.2619            | 0.3438         | 0.2973     | 0.6364            | 0.4828         | 0.5490     | 0.5513       | 0.6353          |
| 0.0648        | 11.0  | 1375 | 0.2660          | 0.6280    | 0.6794 | 0.6527 | 0.9353   | 0.5786        | 0.6454     | 0.6101 | 0.3824            | 0.4062         | 0.3939     | 0.8956         | 0.9056      | 0.9006  | 0.2812            | 0.2812         | 0.2812     | 0.5484            | 0.5862         | 0.5667     | 0.5505       | 0.6544          |
| 0.0284        | 12.0  | 1500 | 0.2819          | 0.6366    | 0.6702 | 0.6530 | 0.9355   | 0.5827        | 0.6392     | 0.6096 | 0.5               | 0.1875         | 0.2727     | 0.8956         | 0.9056      | 0.9006  | 0.3478            | 0.5            | 0.4103     | 0.5               | 0.4483         | 0.4727     | 0.5332       | 0.6508          |
| 0.0284        | 13.0  | 1625 | 0.3000          | 0.6326    | 0.6702 | 0.6509 | 0.9363   | 0.5736        | 0.6351     | 0.6027 | 0.4444            | 0.375          | 0.4068     | 0.8950         | 0.9         | 0.8975  | 0.3421            | 0.4062         | 0.3714     | 0.65              | 0.4483         | 0.5306     | 0.5618       | 0.6519          |
| 0.0284        | 14.0  | 1750 | 0.2996          | 0.6228    | 0.6491 | 0.6357 | 0.9363   | 0.5645        | 0.6041     | 0.5837 | 0.4783            | 0.3438         | 0.4        | 0.8743         | 0.8889      | 0.8815  | 0.2973            | 0.3438         | 0.3188     | 0.6071            | 0.5862         | 0.5965     | 0.5561       | 0.6360          |
| 0.0284        | 15.0  | 1875 | 0.3246          | 0.6311    | 0.6636 | 0.6469 | 0.9352   | 0.5788        | 0.6206     | 0.5990 | 0.45              | 0.2812         | 0.3462     | 0.9056         | 0.9056      | 0.9056  | 0.2683            | 0.3438         | 0.3014     | 0.5278            | 0.6552         | 0.5846     | 0.5473       | 0.6480          |
| 0.0136        | 16.0  | 2000 | 0.3305          | 0.6461    | 0.6623 | 0.6541 | 0.9377   | 0.5869        | 0.6268     | 0.6062 | 0.4545            | 0.3125         | 0.3704     | 0.9011         | 0.9111      | 0.9061  | 0.3448            | 0.3125         | 0.3279     | 0.5385            | 0.4828         | 0.5091     | 0.5439       | 0.6520          |
| 0.0136        | 17.0  | 2125 | 0.3181          | 0.6291    | 0.6781 | 0.6527 | 0.9375   | 0.5780        | 0.6495     | 0.6117 | 0.4231            | 0.3438         | 0.3793     | 0.9066         | 0.9167      | 0.9116  | 0.2857            | 0.3125         | 0.2985     | 0.4483            | 0.4483         | 0.4483     | 0.5299       | 0.6536          |
| 0.0136        | 18.0  | 2250 | 0.3414          | 0.6298    | 0.6755 | 0.6518 | 0.9362   | 0.5765        | 0.6371     | 0.6053 | 0.375             | 0.375          | 0.375      | 0.8962         | 0.9111      | 0.9036  | 0.3235            | 0.3438         | 0.3333     | 0.5714            | 0.5517         | 0.5614     | 0.5557       | 0.6532          |
| 0.0136        | 19.0  | 2375 | 0.3457          | 0.6302    | 0.6768 | 0.6527 | 0.9372   | 0.5877        | 0.6495     | 0.6170 | 0.3636            | 0.25           | 0.2963     | 0.8907         | 0.9056      | 0.8981  | 0.26              | 0.4062         | 0.3171     | 0.6087            | 0.4828         | 0.5385     | 0.5334       | 0.6546          |
| 0.0078        | 20.0  | 2500 | 0.3700          | 0.6367    | 0.6636 | 0.6499 | 0.9367   | 0.5805        | 0.6247     | 0.6018 | 0.3714            | 0.4062         | 0.3881     | 0.9016         | 0.9167      | 0.9091  | 0.3077            | 0.25           | 0.2759     | 0.5833            | 0.4828         | 0.5283     | 0.5406       | 0.6492          |
| 0.0078        | 21.0  | 2625 | 0.3772          | 0.6276    | 0.6715 | 0.6488 | 0.9325   | 0.5766        | 0.6289     | 0.6016 | 0.44              | 0.3438         | 0.3860     | 0.8919         | 0.9167      | 0.9041  | 0.2927            | 0.375          | 0.3288     | 0.5161            | 0.5517         | 0.5333     | 0.5508       | 0.6502          |
| 0.0078        | 22.0  | 2750 | 0.3622          | 0.6389    | 0.6768 | 0.6573 | 0.9345   | 0.5855        | 0.6495     | 0.6158 | 0.4333            | 0.4062         | 0.4194     | 0.8840         | 0.8889      | 0.8864  | 0.3333            | 0.3125         | 0.3226     | 0.625             | 0.5172         | 0.5660     | 0.5620       | 0.6575          |
| 0.0078        | 23.0  | 2875 | 0.3811          | 0.6304    | 0.6728 | 0.6509 | 0.9352   | 0.5765        | 0.6371     | 0.6053 | 0.4               | 0.375          | 0.3871     | 0.8804         | 0.9         | 0.8901  | 0.3438            | 0.3438         | 0.3438     | 0.5926            | 0.5517         | 0.5714     | 0.5595       | 0.6514          |
| 0.005         | 24.0  | 3000 | 0.3824          | 0.6322    | 0.6689 | 0.65   | 0.9353   | 0.5757        | 0.6351     | 0.6039 | 0.4286            | 0.375          | 0.4000     | 0.8901         | 0.9         | 0.8950  | 0.3226            | 0.3125         | 0.3175     | 0.5769            | 0.5172         | 0.5455     | 0.5524       | 0.6501          |
| 0.005         | 25.0  | 3125 | 0.3821          | 0.6297    | 0.6821 | 0.6548 | 0.9375   | 0.5850        | 0.6598     | 0.6202 | 0.4               | 0.375          | 0.3871     | 0.8852         | 0.9         | 0.8926  | 0.25              | 0.2812         | 0.2647     | 0.56              | 0.4828         | 0.5185     | 0.5366       | 0.6561          |
| 0.005         | 26.0  | 3250 | 0.4058          | 0.6292    | 0.6715 | 0.6496 | 0.9355   | 0.5821        | 0.6433     | 0.6112 | 0.3939            | 0.4062         | 0.4        | 0.875          | 0.8944      | 0.8846  | 0.2857            | 0.25           | 0.2667     | 0.5357            | 0.5172         | 0.5263     | 0.5378       | 0.6494          |
| 0.005         | 27.0  | 3375 | 0.3980          | 0.6262    | 0.6807 | 0.6523 | 0.9369   | 0.5743        | 0.6536     | 0.6114 | 0.4074            | 0.3438         | 0.3729     | 0.8798         | 0.8944      | 0.8871  | 0.3333            | 0.375          | 0.3529     | 0.5769            | 0.5172         | 0.5455     | 0.5539       | 0.6533          |
| 0.0031        | 28.0  | 3500 | 0.4100          | 0.6305    | 0.6755 | 0.6522 | 0.9351   | 0.5762        | 0.6392     | 0.6061 | 0.4074            | 0.3438         | 0.3729     | 0.8962         | 0.9111      | 0.9036  | 0.3421            | 0.4062         | 0.3714     | 0.5385            | 0.4828         | 0.5091     | 0.5526       | 0.6533          |
| 0.0031        | 29.0  | 3625 | 0.4050          | 0.6383    | 0.6939 | 0.6650 | 0.9388   | 0.5916        | 0.6660     | 0.6266 | 0.44              | 0.3438         | 0.3860     | 0.8913         | 0.9111      | 0.9011  | 0.3095            | 0.4062         | 0.3514     | 0.5556            | 0.5172         | 0.5357     | 0.5601       | 0.6665          |
| 0.0031        | 30.0  | 3750 | 0.4111          | 0.6348    | 0.6741 | 0.6539 | 0.9367   | 0.5819        | 0.6371     | 0.6083 | 0.4138            | 0.375          | 0.3934     | 0.8962         | 0.9111      | 0.9036  | 0.3243            | 0.375          | 0.3478     | 0.56              | 0.4828         | 0.5185     | 0.5543       | 0.6549          |
| 0.0031        | 31.0  | 3875 | 0.4074          | 0.6349    | 0.6768 | 0.6552 | 0.9381   | 0.5832        | 0.6433     | 0.6118 | 0.3846            | 0.3125         | 0.3448     | 0.8962         | 0.9111      | 0.9036  | 0.3333            | 0.4062         | 0.3662     | 0.56              | 0.4828         | 0.5185     | 0.5490       | 0.6559          |
| 0.002         | 32.0  | 4000 | 0.4086          | 0.6421    | 0.6794 | 0.6603 | 0.9379   | 0.5843        | 0.6433     | 0.6124 | 0.4138            | 0.375          | 0.3934     | 0.9016         | 0.9167      | 0.9091  | 0.375             | 0.375          | 0.375      | 0.5833            | 0.4828         | 0.5283     | 0.5636       | 0.6603          |
| 0.002         | 33.0  | 4125 | 0.4174          | 0.6378    | 0.6900 | 0.6629 | 0.9369   | 0.5847        | 0.6619     | 0.6209 | 0.4074            | 0.3438         | 0.3729     | 0.9022         | 0.9222      | 0.9121  | 0.3235            | 0.3438         | 0.3333     | 0.5385            | 0.4828         | 0.5091     | 0.5497       | 0.6632          |
| 0.002         | 34.0  | 4250 | 0.4131          | 0.6431    | 0.6847 | 0.6633 | 0.9379   | 0.5881        | 0.6536     | 0.6191 | 0.4138            | 0.375          | 0.3934     | 0.8962         | 0.9111      | 0.9036  | 0.375             | 0.375          | 0.375      | 0.5833            | 0.4828         | 0.5283     | 0.5639       | 0.6634          |
| 0.002         | 35.0  | 4375 | 0.4142          | 0.6452    | 0.6860 | 0.6650 | 0.9380   | 0.5911        | 0.6557     | 0.6217 | 0.4138            | 0.375          | 0.3934     | 0.8962         | 0.9111      | 0.9036  | 0.375             | 0.375          | 0.375      | 0.5833            | 0.4828         | 0.5283     | 0.5644       | 0.6650          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "roberta-base", "model-index": [{"name": "roberta-base-finetuned-ner-cadec-no-iob", "results": []}]}
transformers tensorboard safetensors roberta token-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us