File size: 3,762 Bytes
d20223a |
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: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: small-e-czech-finetuned-ner-wikiann
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
args: cs
metrics:
- name: Precision
type: precision
value: 0.8713322894683097
- name: Recall
type: recall
value: 0.8970423324922905
- name: F1
type: f1
value: 0.8840004144075699
- name: Accuracy
type: accuracy
value: 0.9557089381093997
---
<!-- 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. -->
# small-e-czech-finetuned-ner-wikiann
This model is a fine-tuned version of [Seznam/small-e-czech](https://huggingface.co/Seznam/small-e-czech) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2547
- Precision: 0.8713
- Recall: 0.8970
- F1: 0.8840
- Accuracy: 0.9557
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2924 | 1.0 | 2500 | 0.2449 | 0.7686 | 0.8088 | 0.7882 | 0.9320 |
| 0.2042 | 2.0 | 5000 | 0.2137 | 0.8050 | 0.8398 | 0.8220 | 0.9400 |
| 0.1699 | 3.0 | 7500 | 0.1912 | 0.8236 | 0.8593 | 0.8411 | 0.9466 |
| 0.1419 | 4.0 | 10000 | 0.1931 | 0.8349 | 0.8671 | 0.8507 | 0.9488 |
| 0.1316 | 5.0 | 12500 | 0.1892 | 0.8470 | 0.8776 | 0.8620 | 0.9519 |
| 0.1042 | 6.0 | 15000 | 0.2058 | 0.8433 | 0.8811 | 0.8618 | 0.9508 |
| 0.0884 | 7.0 | 17500 | 0.2020 | 0.8602 | 0.8849 | 0.8724 | 0.9531 |
| 0.0902 | 8.0 | 20000 | 0.2118 | 0.8551 | 0.8837 | 0.8692 | 0.9528 |
| 0.0669 | 9.0 | 22500 | 0.2171 | 0.8634 | 0.8906 | 0.8768 | 0.9550 |
| 0.0529 | 10.0 | 25000 | 0.2228 | 0.8638 | 0.8912 | 0.8773 | 0.9545 |
| 0.0613 | 11.0 | 27500 | 0.2293 | 0.8626 | 0.8898 | 0.8760 | 0.9544 |
| 0.0549 | 12.0 | 30000 | 0.2276 | 0.8694 | 0.8958 | 0.8824 | 0.9554 |
| 0.0516 | 13.0 | 32500 | 0.2384 | 0.8717 | 0.8940 | 0.8827 | 0.9552 |
| 0.0412 | 14.0 | 35000 | 0.2443 | 0.8701 | 0.8931 | 0.8815 | 0.9554 |
| 0.0345 | 15.0 | 37500 | 0.2464 | 0.8723 | 0.8958 | 0.8839 | 0.9557 |
| 0.0412 | 16.0 | 40000 | 0.2477 | 0.8705 | 0.8948 | 0.8825 | 0.9552 |
| 0.0363 | 17.0 | 42500 | 0.2525 | 0.8742 | 0.8973 | 0.8856 | 0.9559 |
| 0.0341 | 18.0 | 45000 | 0.2529 | 0.8727 | 0.8962 | 0.8843 | 0.9561 |
| 0.0194 | 19.0 | 47500 | 0.2533 | 0.8699 | 0.8966 | 0.8830 | 0.9557 |
| 0.0247 | 20.0 | 50000 | 0.2547 | 0.8713 | 0.8970 | 0.8840 | 0.9557 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
|