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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ner
type: ner
config: indian_names
split: test
args: indian_names
metrics:
- name: Precision
type: precision
value: 1.0
- name: Recall
type: recall
value: 1.0
- name: F1
type: f1
value: 1.0
- name: Accuracy
type: accuracy
value: 1.0
---
<!-- 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 ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
## 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: 5e-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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 344 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0027 | 2.0 | 688 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0019 | 3.0 | 1032 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0019 | 4.0 | 1376 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0021 | 5.0 | 1720 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0016 | 6.0 | 2064 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0016 | 7.0 | 2408 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0007 | 8.0 | 2752 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.001 | 9.0 | 3096 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.001 | 10.0 | 3440 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.001 | 11.0 | 3784 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0008 | 12.0 | 4128 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0008 | 13.0 | 4472 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0007 | 14.0 | 4816 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0009 | 15.0 | 5160 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0006 | 16.0 | 5504 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0006 | 17.0 | 5848 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 18.0 | 6192 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0006 | 19.0 | 6536 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0006 | 20.0 | 6880 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0007 | 21.0 | 7224 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0007 | 22.0 | 7568 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0007 | 23.0 | 7912 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0005 | 24.0 | 8256 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 25.0 | 8600 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 26.0 | 8944 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 27.0 | 9288 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 28.0 | 9632 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 29.0 | 9976 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 30.0 | 10320 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 31.0 | 10664 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 32.0 | 11008 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 33.0 | 11352 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 34.0 | 11696 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 35.0 | 12040 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 36.0 | 12384 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 37.0 | 12728 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 38.0 | 13072 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 39.0 | 13416 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 40.0 | 13760 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 41.0 | 14104 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 42.0 | 14448 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 43.0 | 14792 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 44.0 | 15136 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 45.0 | 15480 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 46.0 | 15824 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 47.0 | 16168 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 48.0 | 16512 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 49.0 | 16856 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 50.0 | 17200 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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