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# finetuned_minilm

This model is a fine-tuned version of [nreimers/MiniLM-L6-H384-uncased](https://huggingface.co/nreimers/MiniLM-L6-H384-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6736
- Accuracy: 0.9023

## 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: 32
- eval_batch_size: 32
- seed: 12345
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5371        | 1.0   | 619   | 0.2941          | 0.8782   |
| 0.2763        | 2.0   | 1238  | 0.2590          | 0.8986   |
| 0.1899        | 3.0   | 1857  | 0.3081          | 0.8959   |
| 0.1257        | 4.0   | 2476  | 0.2576          | 0.9177   |
| 0.0929        | 5.0   | 3095  | 0.3949          | 0.9059   |
| 0.0806        | 6.0   | 3714  | 0.3304          | 0.9173   |
| 0.0629        | 7.0   | 4333  | 0.4214          | 0.9073   |
| 0.0474        | 8.0   | 4952  | 0.4625          | 0.9145   |
| 0.0498        | 9.0   | 5571  | 0.4227          | 0.9236   |
| 0.049         | 10.0  | 6190  | 0.5549          | 0.8945   |
| 0.0411        | 11.0  | 6809  | 0.3340          | 0.9341   |
| 0.0272        | 12.0  | 7428  | 0.3317          | 0.9291   |
| 0.0264        | 13.0  | 8047  | 0.4099          | 0.9305   |
| 0.0279        | 14.0  | 8666  | 0.4092          | 0.9268   |
| 0.0242        | 15.0  | 9285  | 0.4418          | 0.9318   |
| 0.0241        | 16.0  | 9904  | 0.4352          | 0.9273   |
| 0.0238        | 17.0  | 10523 | 0.5306          | 0.9259   |
| 0.0216        | 18.0  | 11142 | 0.4267          | 0.9241   |
| 0.0166        | 19.0  | 11761 | 0.5134          | 0.9255   |
| 0.0182        | 20.0  | 12380 | 0.6736          | 0.9023   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "finetuned_minilm", "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 

finetuned\_minilm
=================


This model is a fine-tuned version of nreimers/MiniLM-L6-H384-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6736
* Accuracy: 0.9023


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: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* 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: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2