File size: 2,788 Bytes
7dcd42e 7317243 7dcd42e 7317243 7dcd42e 7317243 7dcd42e 7317243 5ba5e66 7dcd42e 7317243 7dcd42e 7317243 7dcd42e 7317243 7dcd42e 7317243 7dcd42e | 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 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll2003
metrics:
- name: Precision
type: precision
value: 0.9369817578772802
- name: Recall
type: recall
value: 0.9508582968697409
- name: F1
type: f1
value: 0.9438690277313732
- name: Accuracy
type: accuracy
value: 0.9868575969859305
- task:
type: token-classification
name: Token Classification
dataset:
name: conll2003
type: conll2003
config: conll2003
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.9003955185074297
verified: true
- name: Precision
type: precision
value: 0.9290508149568553
verified: true
- name: Recall
type: recall
value: 0.9157575355638824
verified: true
- name: F1
type: f1
value: 0.9223562810503904
verified: true
- name: loss
type: loss
value: 0.8637956976890564
verified: true
---
<!-- 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. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0598
- Precision: 0.9370
- Recall: 0.9509
- F1: 0.9439
- Accuracy: 0.9869
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0871 | 1.0 | 1756 | 0.0633 | 0.9197 | 0.9362 | 0.9279 | 0.9833 |
| 0.0386 | 2.0 | 3512 | 0.0572 | 0.9351 | 0.9483 | 0.9417 | 0.9866 |
| 0.0214 | 3.0 | 5268 | 0.0598 | 0.9370 | 0.9509 | 0.9439 | 0.9869 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
|