File size: 12,892 Bytes
648d1ba |
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: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-base-discriminator-finetuned-ner-cadec
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. -->
# electra-base-discriminator-finetuned-ner-cadec
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: 0.4364
- Precision: 0.3437
- Recall: 0.2772
- F1: 0.3068
- Accuracy: 0.8714
- Adr Precision: 0.2406
- Adr Recall: 0.2220
- Adr F1: 0.2309
- Disease Precision: 0.0
- Disease Recall: 0.0
- Disease F1: 0.0
- Drug Precision: 0.7063
- Drug Recall: 0.6121
- Drug F1: 0.6558
- 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: 0.5426
- B-adr Recall: 0.3666
- B-adr F1: 0.4376
- B-disease Precision: 0.0
- B-disease Recall: 0.0
- B-disease F1: 0.0
- B-drug Precision: 0.9375
- B-drug Recall: 0.6364
- B-drug F1: 0.7581
- 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: 0.1906
- I-adr Recall: 0.1738
- I-adr F1: 0.1818
- I-disease Precision: 0.0
- I-disease Recall: 0.0
- I-disease F1: 0.0
- I-drug Precision: 0.7343
- I-drug Recall: 0.6442
- I-drug F1: 0.6863
- 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: 0.2064
- Weighted Avg F1: 0.3770
## 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 | 0.8387 | 0.0 | 0.0 | 0.0 | 0.7902 | 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 | 254 | 0.8358 | 0.0 | 0.0 | 0.0 | 0.7902 | 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 | 3.0 | 381 | 0.7415 | 0.0782 | 0.0512 | 0.0619 | 0.7906 | 0.0782 | 0.0752 | 0.0767 | 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 | 0.0172 | 0.0203 | 0.0186 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0019 | 0.0057 |
| 0.8638 | 4.0 | 508 | 0.6493 | 0.1417 | 0.0637 | 0.0879 | 0.8160 | 0.1417 | 0.0936 | 0.1127 | 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 | 0.0253 | 0.0203 | 0.0225 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0023 | 0.0069 |
| 0.8638 | 5.0 | 635 | 0.5528 | 0.3498 | 0.2122 | 0.2642 | 0.8489 | 0.2037 | 0.1431 | 0.1681 | 0.0 | 0.0 | 0.0 | 0.8932 | 0.5576 | 0.6866 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5104 | 0.0940 | 0.1588 | 0.0 | 0.0 | 0.0 | 0.9444 | 0.4121 | 0.5738 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0760 | 0.0587 | 0.0662 | 0.0 | 0.0 | 0.0 | 0.68 | 0.4172 | 0.5171 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1316 | 0.2012 |
| 0.8638 | 6.0 | 762 | 0.4846 | 0.2864 | 0.2310 | 0.2557 | 0.8587 | 0.1698 | 0.1670 | 0.1684 | 0.0 | 0.0 | 0.0 | 0.8545 | 0.5697 | 0.6836 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5070 | 0.2764 | 0.3578 | 0.0 | 0.0 | 0.0 | 0.9604 | 0.5879 | 0.7293 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1170 | 0.1151 | 0.1160 | 0.0 | 0.0 | 0.0 | 0.8818 | 0.5951 | 0.7106 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1914 | 0.3276 |
| 0.8638 | 7.0 | 889 | 0.4610 | 0.3376 | 0.2622 | 0.2952 | 0.8679 | 0.2253 | 0.2092 | 0.2169 | 0.0 | 0.0 | 0.0 | 0.8276 | 0.5818 | 0.6833 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5228 | 0.2860 | 0.3697 | 0.0 | 0.0 | 0.0 | 0.9519 | 0.6 | 0.7361 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1734 | 0.1648 | 0.1690 | 0.0 | 0.0 | 0.0 | 0.8696 | 0.6135 | 0.7194 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1994 | 0.3498 |
| 0.5419 | 8.0 | 1016 | 0.4499 | 0.2983 | 0.2697 | 0.2833 | 0.8656 | 0.1976 | 0.2128 | 0.2049 | 0.0 | 0.0 | 0.0 | 0.7299 | 0.6061 | 0.6623 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4803 | 0.3743 | 0.4207 | 0.0 | 0.0 | 0.0 | 0.9369 | 0.6303 | 0.7536 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1738 | 0.1828 | 0.1782 | 0.0 | 0.0 | 0.0 | 0.7518 | 0.6319 | 0.6867 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2039 | 0.3693 |
| 0.5419 | 9.0 | 1143 | 0.4511 | 0.3544 | 0.2734 | 0.3087 | 0.8700 | 0.2418 | 0.2165 | 0.2285 | 0.0 | 0.0 | 0.0 | 0.7769 | 0.6121 | 0.6847 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5203 | 0.3436 | 0.4139 | 0.0 | 0.0 | 0.0 | 0.9211 | 0.6364 | 0.7527 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2041 | 0.1783 | 0.1904 | 0.0 | 0.0 | 0.0 | 0.7907 | 0.6258 | 0.6986 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2056 | 0.3718 |
| 0.5419 | 10.0 | 1270 | 0.4364 | 0.3437 | 0.2772 | 0.3068 | 0.8714 | 0.2406 | 0.2220 | 0.2309 | 0.0 | 0.0 | 0.0 | 0.7063 | 0.6121 | 0.6558 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5426 | 0.3666 | 0.4376 | 0.0 | 0.0 | 0.0 | 0.9375 | 0.6364 | 0.7581 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1906 | 0.1738 | 0.1818 | 0.0 | 0.0 | 0.0 | 0.7343 | 0.6442 | 0.6863 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2064 | 0.3770 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|