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# laptop_sentence_classfication_wangChanBERTa

This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2752
- Accuracy: 0.9

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 25   | 0.6130          | 0.7077   |
| No log        | 2.0   | 50   | 0.4832          | 0.7769   |
| No log        | 3.0   | 75   | 0.4457          | 0.8154   |
| No log        | 4.0   | 100  | 0.4696          | 0.7692   |
| No log        | 5.0   | 125  | 0.4378          | 0.8077   |
| No log        | 6.0   | 150  | 0.4698          | 0.8077   |
| No log        | 7.0   | 175  | 0.3654          | 0.8615   |
| No log        | 8.0   | 200  | 0.3795          | 0.8615   |
| No log        | 9.0   | 225  | 0.4212          | 0.8692   |
| No log        | 10.0  | 250  | 0.4153          | 0.8538   |
| No log        | 11.0  | 275  | 0.3723          | 0.8692   |
| No log        | 12.0  | 300  | 0.3590          | 0.8538   |
| No log        | 13.0  | 325  | 0.2553          | 0.9077   |
| No log        | 14.0  | 350  | 0.2713          | 0.9      |
| No log        | 15.0  | 375  | 0.2699          | 0.9077   |
| No log        | 16.0  | 400  | 0.2563          | 0.9154   |
| No log        | 17.0  | 425  | 0.2536          | 0.9231   |
| No log        | 18.0  | 450  | 0.2529          | 0.9154   |
| No log        | 19.0  | 475  | 0.2743          | 0.9      |
| 0.3025        | 20.0  | 500  | 0.2752          | 0.9      |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "laptop_sentence_classfication_wangChanBERTa", "results": []}]}
transformers pytorch tensorboard camembert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

laptop\_sentence\_classfication\_wangChanBERTa
==============================================


This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2752
* Accuracy: 0.9


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: 20


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### 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: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3