Commit
·
91a0946
1
Parent(s):
afdc3c8
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,84 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- precision
|
| 7 |
+
- recall
|
| 8 |
+
- f1
|
| 9 |
+
- accuracy
|
| 10 |
+
model-index:
|
| 11 |
+
- name: ner_column_bert-base-NER
|
| 12 |
+
results: []
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 16 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 17 |
+
|
| 18 |
+
# ner_column_bert-base-NER
|
| 19 |
+
|
| 20 |
+
This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the None dataset.
|
| 21 |
+
It achieves the following results on the evaluation set:
|
| 22 |
+
- Loss: 0.1872
|
| 23 |
+
- Precision: 0.7623
|
| 24 |
+
- Recall: 0.7753
|
| 25 |
+
- F1: 0.7688
|
| 26 |
+
- Accuracy: 0.9023
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 2e-05
|
| 46 |
+
- train_batch_size: 64
|
| 47 |
+
- eval_batch_size: 64
|
| 48 |
+
- seed: 42
|
| 49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 50 |
+
- lr_scheduler_type: linear
|
| 51 |
+
- num_epochs: 20
|
| 52 |
+
|
| 53 |
+
### Training results
|
| 54 |
+
|
| 55 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 56 |
+
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 57 |
+
| No log | 1.0 | 702 | 0.6427 | 0.3025 | 0.2180 | 0.2534 | 0.7415 |
|
| 58 |
+
| 0.9329 | 2.0 | 1404 | 0.4771 | 0.4343 | 0.3587 | 0.3929 | 0.7955 |
|
| 59 |
+
| 0.546 | 3.0 | 2106 | 0.3983 | 0.5157 | 0.4530 | 0.4823 | 0.8242 |
|
| 60 |
+
| 0.546 | 4.0 | 2808 | 0.3748 | 0.5089 | 0.4758 | 0.4918 | 0.8305 |
|
| 61 |
+
| 0.4339 | 5.0 | 3510 | 0.2947 | 0.6362 | 0.6146 | 0.6252 | 0.8656 |
|
| 62 |
+
| 0.3658 | 6.0 | 4212 | 0.2818 | 0.6421 | 0.6231 | 0.6325 | 0.8664 |
|
| 63 |
+
| 0.3658 | 7.0 | 4914 | 0.2459 | 0.7108 | 0.6983 | 0.7045 | 0.8834 |
|
| 64 |
+
| 0.3221 | 8.0 | 5616 | 0.2665 | 0.6586 | 0.6404 | 0.6494 | 0.8701 |
|
| 65 |
+
| 0.2914 | 9.0 | 6318 | 0.2449 | 0.6880 | 0.6768 | 0.6823 | 0.8793 |
|
| 66 |
+
| 0.2657 | 10.0 | 7020 | 0.2411 | 0.7014 | 0.6862 | 0.6937 | 0.8824 |
|
| 67 |
+
| 0.2657 | 11.0 | 7722 | 0.2179 | 0.7261 | 0.7228 | 0.7244 | 0.8902 |
|
| 68 |
+
| 0.2453 | 12.0 | 8424 | 0.2301 | 0.6922 | 0.6919 | 0.6920 | 0.8858 |
|
| 69 |
+
| 0.2295 | 13.0 | 9126 | 0.2352 | 0.6768 | 0.6836 | 0.6802 | 0.8832 |
|
| 70 |
+
| 0.2295 | 14.0 | 9828 | 0.2020 | 0.7545 | 0.7499 | 0.7522 | 0.8970 |
|
| 71 |
+
| 0.2155 | 15.0 | 10530 | 0.2012 | 0.7449 | 0.7508 | 0.7478 | 0.8974 |
|
| 72 |
+
| 0.2064 | 16.0 | 11232 | 0.2036 | 0.7282 | 0.7402 | 0.7341 | 0.8960 |
|
| 73 |
+
| 0.2064 | 17.0 | 11934 | 0.1976 | 0.7390 | 0.7496 | 0.7443 | 0.8974 |
|
| 74 |
+
| 0.1978 | 18.0 | 12636 | 0.1859 | 0.7688 | 0.7828 | 0.7757 | 0.9040 |
|
| 75 |
+
| 0.1895 | 19.0 | 13338 | 0.1917 | 0.7574 | 0.7691 | 0.7632 | 0.9014 |
|
| 76 |
+
| 0.186 | 20.0 | 14040 | 0.1872 | 0.7623 | 0.7753 | 0.7688 | 0.9023 |
|
| 77 |
+
|
| 78 |
+
|
| 79 |
+
### Framework versions
|
| 80 |
+
|
| 81 |
+
- Transformers 4.30.2
|
| 82 |
+
- Pytorch 1.13.1+cu116
|
| 83 |
+
- Datasets 2.13.2
|
| 84 |
+
- Tokenizers 0.13.3
|