File size: 12,868 Bytes
03802b4 93ae107 03802b4 93ae107 03802b4 93ae107 03802b4 93ae107 03802b4 93ae107 03802b4 93ae107 03802b4 93ae107 03802b4 93ae107 03802b4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 |
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner-cadec-active
results: []
---
<!-- 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. -->
# distilbert-base-uncased-finetuned-ner-cadec-active
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3960
- Precision: 0.4297
- Recall: 0.3910
- F1: 0.4094
- Accuracy: 0.8851
- Adr Precision: 0.3380
- Adr Recall: 0.3474
- Adr F1: 0.3427
- Disease Precision: 0.0
- Disease Recall: 0.0
- Disease F1: 0.0
- Drug Precision: 0.7857
- Drug Recall: 0.7606
- Drug F1: 0.7730
- Finding Precision: 0.0
- Finding Recall: 0.0
- Finding F1: 0.0
- Symptom Precision: 0.0
- Symptom Recall: 0.0
- Symptom F1: 0.0
- B-adr Precision: 0.6115
- B-adr Recall: 0.4189
- B-adr F1: 0.4972
- B-disease Precision: 0.0
- B-disease Recall: 0.0
- B-disease F1: 0.0
- B-drug Precision: 0.9605
- B-drug Recall: 0.7766
- B-drug F1: 0.8588
- B-finding Precision: 0.0
- B-finding Recall: 0.0
- B-finding F1: 0.0
- B-symptom Precision: 0.0
- B-symptom Recall: 0.0
- B-symptom F1: 0.0
- I-adr Precision: 0.2584
- I-adr Recall: 0.2621
- I-adr F1: 0.2602
- I-disease Precision: 0.0
- I-disease Recall: 0.0
- I-disease F1: 0.0
- I-drug Precision: 0.8362
- I-drug Recall: 0.7914
- I-drug F1: 0.8132
- 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: 0.2429
- Weighted Avg F1: 0.4447
## 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 | 16 | 0.8678 | 0.0 | 0.0 | 0.0 | 0.7876 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 32 | 0.6019 | 0.1340 | 0.0665 | 0.0889 | 0.8179 | 0.1340 | 0.0945 | 0.1108 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0742 | 0.0646 | 0.0691 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0069 | 0.0221 |
| No log | 3.0 | 48 | 0.5072 | 0.2736 | 0.1812 | 0.2180 | 0.8520 | 0.2615 | 0.1991 | 0.2261 | 0.0 | 0.0 | 0.0 | 0.3252 | 0.2128 | 0.2572 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4828 | 0.0220 | 0.0422 | 0.0 | 0.0 | 0.0 | 0.9837 | 0.6436 | 0.7781 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0870 | 0.0808 | 0.0838 | 0.0 | 0.0 | 0.0 | 0.9756 | 0.2139 | 0.3509 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1255 | 0.1639 |
| No log | 4.0 | 64 | 0.4559 | 0.3937 | 0.3050 | 0.3437 | 0.8617 | 0.2798 | 0.2558 | 0.2673 | 0.0 | 0.0 | 0.0 | 0.9531 | 0.6489 | 0.7722 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4340 | 0.0362 | 0.0669 | 0.0 | 0.0 | 0.0 | 0.9843 | 0.6649 | 0.7937 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0882 | 0.0969 | 0.0924 | 0.0 | 0.0 | 0.0 | 0.9685 | 0.6578 | 0.7834 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1736 | 0.2238 |
| No log | 5.0 | 80 | 0.4265 | 0.3860 | 0.3275 | 0.3544 | 0.8675 | 0.2885 | 0.2834 | 0.2859 | 0.0 | 0.0 | 0.0 | 0.8170 | 0.6649 | 0.7331 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5561 | 0.1638 | 0.2530 | 0.0 | 0.0 | 0.0 | 0.9845 | 0.6755 | 0.8013 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1221 | 0.1346 | 0.1281 | 0.0 | 0.0 | 0.0 | 0.8627 | 0.7059 | 0.7765 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1959 | 0.3032 |
| No log | 6.0 | 96 | 0.4091 | 0.3964 | 0.3388 | 0.3653 | 0.8748 | 0.2965 | 0.2922 | 0.2943 | 0.0 | 0.0 | 0.0 | 0.8280 | 0.6915 | 0.7536 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5956 | 0.2551 | 0.3572 | 0.0 | 0.0 | 0.0 | 0.9852 | 0.7074 | 0.8235 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1712 | 0.1813 | 0.1761 | 0.0 | 0.0 | 0.0 | 0.8599 | 0.7219 | 0.7849 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2142 | 0.3599 |
| No log | 7.0 | 112 | 0.4000 | 0.3940 | 0.3521 | 0.3719 | 0.8768 | 0.2999 | 0.3038 | 0.3018 | 0.0 | 0.0 | 0.0 | 0.7670 | 0.7181 | 0.7418 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6077 | 0.2976 | 0.3996 | 0.0 | 0.0 | 0.0 | 0.9718 | 0.7340 | 0.8364 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1853 | 0.1993 | 0.1920 | 0.0 | 0.0 | 0.0 | 0.8343 | 0.7807 | 0.8066 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2235 | 0.3841 |
| No log | 8.0 | 128 | 0.4010 | 0.4306 | 0.3715 | 0.3989 | 0.8816 | 0.3363 | 0.3314 | 0.3338 | 0.0 | 0.0 | 0.0 | 0.8182 | 0.7181 | 0.7649 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.616 | 0.3638 | 0.4574 | 0.0 | 0.0 | 0.0 | 0.9789 | 0.7394 | 0.8424 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2316 | 0.2316 | 0.2316 | 0.0 | 0.0 | 0.0 | 0.8598 | 0.7540 | 0.8034 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2335 | 0.4182 |
| No log | 9.0 | 144 | 0.3963 | 0.4247 | 0.3869 | 0.4049 | 0.8839 | 0.3315 | 0.3430 | 0.3371 | 0.0 | 0.0 | 0.0 | 0.7978 | 0.7553 | 0.7760 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6047 | 0.4047 | 0.4849 | 0.0 | 0.0 | 0.0 | 0.9669 | 0.7766 | 0.8614 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2483 | 0.2549 | 0.2516 | 0.0 | 0.0 | 0.0 | 0.8497 | 0.7861 | 0.8167 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2414 | 0.4381 |
| No log | 10.0 | 160 | 0.3960 | 0.4297 | 0.3910 | 0.4094 | 0.8851 | 0.3380 | 0.3474 | 0.3427 | 0.0 | 0.0 | 0.0 | 0.7857 | 0.7606 | 0.7730 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6115 | 0.4189 | 0.4972 | 0.0 | 0.0 | 0.0 | 0.9605 | 0.7766 | 0.8588 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2584 | 0.2621 | 0.2602 | 0.0 | 0.0 | 0.0 | 0.8362 | 0.7914 | 0.8132 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2429 | 0.4447 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|