File size: 2,194 Bytes
95ca6c0 f78ecf5 95ca6c0 f78ecf5 95ca6c0 f78ecf5 95ca6c0 f78ecf5 95ca6c0 f78ecf5 f8a1385 95ca6c0 f78ecf5 95ca6c0 f78ecf5 95ca6c0 | 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 | ---
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
config: conll2003
split: validation
args: conll2003
metrics:
- name: Precision
type: precision
value: 0.9328493647912885
- name: Recall
type: recall
value: 0.9515314708852238
- name: F1
type: f1
value: 0.942097808881113
- name: Accuracy
type: accuracy
value: 0.9865632542532525
---
<!-- 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: 0.0591
- Precision: 0.9328
- Recall: 0.9515
- F1: 0.9421
- Accuracy: 0.9866
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.088 | 1.0 | 1756 | 0.0673 | 0.9190 | 0.9334 | 0.9261 | 0.9823 |
| 0.0346 | 2.0 | 3512 | 0.0611 | 0.9284 | 0.9477 | 0.9380 | 0.9855 |
| 0.0178 | 3.0 | 5268 | 0.0591 | 0.9328 | 0.9515 | 0.9421 | 0.9866 |
### Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
|