
<!-- 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. -->

# mobilebert-uncased-finetuned-ner

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the id_nergrit_corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3800
- Precision: 0.6700
- Recall: 0.6136
- F1: 0.6406
- Accuracy: 0.8974

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6239        | 1.0   | 1567 | 0.4989          | 0.5842    | 0.4877 | 0.5316 | 0.8688   |
| 0.5356        | 2.0   | 3134 | 0.4003          | 0.6368    | 0.5879 | 0.6113 | 0.8905   |
| 0.4035        | 3.0   | 4701 | 0.3800          | 0.6700    | 0.6136 | 0.6406 | 0.8974   |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["id_nergrit_corpus"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "mobilebert-uncased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "id_nergrit_corpus", "type": "id_nergrit_corpus", "config": "ner", "split": "validation", "args": "ner"}, "metrics": [{"type": "precision", "value": 0.6699979179679367, "name": "Precision"}, {"type": "recall", "value": 0.6136244458216141, "name": "Recall"}, {"type": "f1", "value": 0.6405732911990843, "name": "F1"}, {"type": "accuracy", "value": 0.8974442203210374, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard mobilebert token-classification generated_from_trainer dataset:id_nergrit_corpus license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #mobilebert #token-classification #generated_from_trainer #dataset-id_nergrit_corpus #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

mobilebert-uncased-finetuned-ner
================================


This model is a fine-tuned version of google/mobilebert-uncased on the id\_nergrit\_corpus dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3800
* Precision: 0.6700
* Recall: 0.6136
* F1: 0.6406
* Accuracy: 0.8974


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: 3


### Training results



### Framework versions


* Transformers 4.29.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 3 ### Training results ### Framework versions


* Transformers 4.29.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #mobilebert #token-classification #generated_from_trainer #dataset-id_nergrit_corpus #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### 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: 3 ### Training results ### Framework versions


* Transformers 4.29.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3