
<!-- 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. -->

# mongolian-gpt2-ner-finetuning

This model is a fine-tuned version of [bayartsogt/mongolian-gpt2](https://huggingface.co/bayartsogt/mongolian-gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3230
- Precision: 0.0989
- Recall: 0.2277
- F1: 0.1380
- Accuracy: 0.9078

## 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: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5225        | 1.0   | 477  | 0.3650          | 0.0743    | 0.1674 | 0.1030 | 0.8821   |
| 0.322         | 2.0   | 954  | 0.3129          | 0.0853    | 0.1903 | 0.1178 | 0.8966   |
| 0.2681        | 3.0   | 1431 | 0.3008          | 0.0915    | 0.2034 | 0.1262 | 0.9022   |
| 0.232         | 4.0   | 1908 | 0.2963          | 0.0914    | 0.2070 | 0.1269 | 0.9053   |
| 0.2029        | 5.0   | 2385 | 0.2974          | 0.0933    | 0.2120 | 0.1295 | 0.9071   |
| 0.1791        | 6.0   | 2862 | 0.3038          | 0.0949    | 0.2140 | 0.1315 | 0.9076   |
| 0.1603        | 7.0   | 3339 | 0.3100          | 0.0958    | 0.2186 | 0.1332 | 0.9079   |
| 0.146         | 8.0   | 3816 | 0.3174          | 0.0950    | 0.2156 | 0.1319 | 0.9079   |
| 0.1355        | 9.0   | 4293 | 0.3233          | 0.1001    | 0.2274 | 0.1390 | 0.9080   |
| 0.1291        | 10.0  | 4770 | 0.3230          | 0.0989    | 0.2277 | 0.1380 | 0.9078   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["mn"], "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "mongolian-gpt2-ner-finetuning", "results": []}]}
transformers pytorch tensorboard gpt2 token-classification generated_from_trainer mn autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #mn #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mongolian-gpt2-ner-finetuning
=============================


This model is a fine-tuned version of bayartsogt/mongolian-gpt2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3230
* Precision: 0.0989
* Recall: 0.2277
* F1: 0.1380
* Accuracy: 0.9078


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: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* 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: 16
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #mn #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3