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# minilm-finetuned-yelp

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1838
- F1: 0.9467

## 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: 5e-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: 15

### Training results

| Training Loss | Epoch | Step   | Validation Loss | F1     |
|:-------------:|:-----:|:------:|:---------------:|:------:|
| 0.858         | 1.0   | 15565  | 0.7554          | 0.6474 |
| 0.7528        | 2.0   | 31130  | 0.6906          | 0.6960 |
| 0.7071        | 3.0   | 46695  | 0.6578          | 0.7273 |
| 0.6654        | 4.0   | 62260  | 0.5850          | 0.7585 |
| 0.6229        | 5.0   | 77825  | 0.5386          | 0.7825 |
| 0.5796        | 6.0   | 93390  | 0.4821          | 0.8188 |
| 0.5367        | 7.0   | 108955 | 0.4254          | 0.8423 |
| 0.4962        | 8.0   | 124520 | 0.3792          | 0.8696 |
| 0.4574        | 9.0   | 140085 | 0.3364          | 0.8843 |
| 0.4222        | 10.0  | 155650 | 0.2893          | 0.9042 |
| 0.3903        | 11.0  | 171215 | 0.2582          | 0.9167 |
| 0.3626        | 12.0  | 186780 | 0.2286          | 0.9283 |
| 0.3386        | 13.0  | 202345 | 0.2029          | 0.9392 |
| 0.3213        | 14.0  | 217910 | 0.1912          | 0.9443 |
| 0.3063        | 15.0  | 233475 | 0.1838          | 0.9467 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "minilm-finetuned-yelp", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

minilm-finetuned-yelp
=====================


This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1838
* F1: 0.9467


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: 5e-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: 15


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 15 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 15 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 15### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2