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# bert-small-unidic-bpe2

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5665
- Accuracy: 0.6690

## 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: 0.0001
- train_batch_size: 768
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 14
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.111         | 1.0   | 69473  | 1.9831          | 0.6056   |
| 1.9667        | 2.0   | 138946 | 1.8334          | 0.6277   |
| 1.8918        | 3.0   | 208419 | 1.7656          | 0.6376   |
| 1.8518        | 4.0   | 277892 | 1.7219          | 0.6444   |
| 1.8202        | 5.0   | 347365 | 1.6904          | 0.6490   |
| 1.7996        | 6.0   | 416838 | 1.6705          | 0.6524   |
| 1.7767        | 7.0   | 486311 | 1.6479          | 0.6558   |
| 1.7663        | 8.0   | 555784 | 1.6339          | 0.6577   |
| 1.7524        | 9.0   | 625257 | 1.6159          | 0.6611   |
| 1.7398        | 10.0  | 694730 | 1.6020          | 0.6627   |
| 1.7229        | 11.0  | 764203 | 1.5920          | 0.6645   |
| 1.7127        | 12.0  | 833676 | 1.5836          | 0.6658   |
| 1.7011        | 13.0  | 903149 | 1.5737          | 0.6677   |
| 1.7           | 14.0  | 972622 | 1.5665          | 0.6690   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert-small-unidic-bpe2", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert-small-unidic-bpe2
======================


This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5665
* Accuracy: 0.6690


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: 0.0001
* train\_batch\_size: 768
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 14
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 768
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 14
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 768
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 14
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 768
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 14
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2