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# electra-small-finetuned-malay-english

This model is a fine-tuned version of [Hazqeel/electra-small-finetuned-sst2-rotten_tomatoes-distilled](https://huggingface.co/Hazqeel/electra-small-finetuned-sst2-rotten_tomatoes-distilled) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2274
- Accuracy: 0.9392

## 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: 0.00012157861764282722
- train_batch_size: 32
- eval_batch_size: 32
- seed: 39
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1491        | 1.0   | 8431  | 0.2398          | 0.9217   |
| 0.13          | 2.0   | 16862 | 0.1834          | 0.9343   |
| 0.0965        | 3.0   | 25293 | 0.2274          | 0.9392   |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.12.1
{"language": ["en", "ms"], "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "electra-small-finetuned-malay-english", "results": []}]}
transformers pytorch tensorboard electra text-classification generated_from_trainer en ms autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #en #ms #autotrain_compatible #endpoints_compatible #region-us 

electra-small-finetuned-malay-english
=====================================


This model is a fine-tuned version of Hazqeel/electra-small-finetuned-sst2-rotten\_tomatoes-distilled on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2274
* Accuracy: 0.9392


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: 0.00012157861764282722
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 39
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00012157861764282722
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 39
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #en #ms #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00012157861764282722
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 39
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #en #ms #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00012157861764282722
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 39
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.1
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.12.1