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End of training
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---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- wnut_17
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_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: 0.55
- name: Recall
type: recall
value: 0.37720111214087115
- name: F1
type: f1
value: 0.44749862561847165
- name: Accuracy
type: accuracy
value: 0.9481063520560827
---
<!-- 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. -->
# my_awesome_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: 0.3958
- Precision: 0.55
- Recall: 0.3772
- F1: 0.4475
- Accuracy: 0.9481
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 213 | 0.2562 | 0.5704 | 0.2929 | 0.3870 | 0.9417 |
| No log | 2.0 | 426 | 0.2776 | 0.5462 | 0.3179 | 0.4019 | 0.9436 |
| 0.1469 | 3.0 | 639 | 0.2834 | 0.5453 | 0.3624 | 0.4354 | 0.9475 |
| 0.1469 | 4.0 | 852 | 0.3004 | 0.5669 | 0.3652 | 0.4442 | 0.9480 |
| 0.0325 | 5.0 | 1065 | 0.3360 | 0.5858 | 0.3735 | 0.4561 | 0.9482 |
| 0.0325 | 6.0 | 1278 | 0.3471 | 0.5149 | 0.3855 | 0.4409 | 0.9474 |
| 0.0325 | 7.0 | 1491 | 0.3883 | 0.5552 | 0.3633 | 0.4392 | 0.9474 |
| 0.0117 | 8.0 | 1704 | 0.3881 | 0.5602 | 0.3707 | 0.4462 | 0.9477 |
| 0.0117 | 9.0 | 1917 | 0.4008 | 0.5582 | 0.3689 | 0.4442 | 0.9478 |
| 0.0051 | 10.0 | 2130 | 0.3958 | 0.55 | 0.3772 | 0.4475 | 0.9481 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0