File size: 3,622 Bytes
cfc4dbc d9df21f cfc4dbc 4bad815 cfc4dbc |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
config: en
split: train
args: en
metrics:
- name: Precision
type: precision
value: 0.8326536254925002
- name: Recall
type: recall
value: 0.8515481408171921
- name: F1
type: f1
value: 0.8419948974242476
- name: Accuracy
type: accuracy
value: 0.934650342703884
---
<!-- 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-base-multilingual-cased-finetuned-ner
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2299
- Precision: 0.8327
- Recall: 0.8515
- F1: 0.8420
- Accuracy: 0.9347
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6617 | 0.16 | 100 | 0.3490 | 0.7259 | 0.7730 | 0.7487 | 0.8983 |
| 0.341 | 0.32 | 200 | 0.2942 | 0.7665 | 0.8052 | 0.7854 | 0.9121 |
| 0.3052 | 0.48 | 300 | 0.2821 | 0.7694 | 0.8021 | 0.7854 | 0.9152 |
| 0.2938 | 0.64 | 400 | 0.2700 | 0.7897 | 0.8122 | 0.8008 | 0.9206 |
| 0.2685 | 0.8 | 500 | 0.2482 | 0.7901 | 0.8253 | 0.8073 | 0.9242 |
| 0.2622 | 0.96 | 600 | 0.2478 | 0.7989 | 0.8298 | 0.8141 | 0.9250 |
| 0.2154 | 1.12 | 700 | 0.2456 | 0.8126 | 0.8365 | 0.8244 | 0.9273 |
| 0.2046 | 1.28 | 800 | 0.2429 | 0.8079 | 0.8335 | 0.8205 | 0.9270 |
| 0.2114 | 1.44 | 900 | 0.2377 | 0.8125 | 0.8415 | 0.8268 | 0.9300 |
| 0.2111 | 1.6 | 1000 | 0.2381 | 0.8231 | 0.8397 | 0.8313 | 0.9309 |
| 0.1934 | 1.76 | 1100 | 0.2349 | 0.8179 | 0.8485 | 0.8329 | 0.9308 |
| 0.1972 | 1.92 | 1200 | 0.2293 | 0.8287 | 0.8446 | 0.8366 | 0.9332 |
| 0.1858 | 2.08 | 1300 | 0.2366 | 0.8280 | 0.8463 | 0.8371 | 0.9327 |
| 0.1506 | 2.24 | 1400 | 0.2392 | 0.8255 | 0.8505 | 0.8378 | 0.9332 |
| 0.1508 | 2.4 | 1500 | 0.2346 | 0.8266 | 0.8465 | 0.8364 | 0.9334 |
| 0.1674 | 2.56 | 1600 | 0.2329 | 0.8249 | 0.8487 | 0.8366 | 0.9329 |
| 0.1584 | 2.72 | 1700 | 0.2309 | 0.8316 | 0.8508 | 0.8411 | 0.9341 |
| 0.154 | 2.88 | 1800 | 0.2299 | 0.8327 | 0.8515 | 0.8420 | 0.9347 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
|