File size: 2,582 Bytes
14e87ea |
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 |
---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- wnut_17
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert_wnut_model
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wnut_17
type: wnut_17
config: wnut_17
split: test
args: wnut_17
metrics:
- name: Precision
type: precision
value: 0.5291073738680466
- name: Recall
type: recall
value: 0.3790546802594995
- name: F1
type: f1
value: 0.44168466522678185
- name: Accuracy
type: accuracy
value: 0.9476788920235958
---
<!-- 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_wnut_model
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3346
- Precision: 0.5291
- Recall: 0.3791
- F1: 0.4417
- Accuracy: 0.9477
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 213 | 0.2607 | 0.5443 | 0.2901 | 0.3785 | 0.9411 |
| No log | 2.0 | 426 | 0.2689 | 0.5474 | 0.3318 | 0.4132 | 0.9453 |
| 0.1554 | 3.0 | 639 | 0.2896 | 0.5253 | 0.3753 | 0.4378 | 0.9475 |
| 0.1554 | 4.0 | 852 | 0.3009 | 0.5079 | 0.3865 | 0.4389 | 0.9474 |
| 0.0349 | 5.0 | 1065 | 0.3195 | 0.5109 | 0.3920 | 0.4436 | 0.9486 |
| 0.0349 | 6.0 | 1278 | 0.3346 | 0.5291 | 0.3791 | 0.4417 | 0.9477 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
|