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# BertWhyCommitOriginal

This model is a fine-tuned version of [prajjwal1/bert-small](https://huggingface.co/prajjwal1/bert-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4881
- Accuracy: 0.8788

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 31   | 0.5058          | 0.7394   |
| No log        | 2.0   | 62   | 0.4463          | 0.7758   |
| No log        | 3.0   | 93   | 0.4260          | 0.7758   |
| No log        | 4.0   | 124  | 0.3954          | 0.8061   |
| No log        | 5.0   | 155  | 0.3745          | 0.8061   |
| No log        | 6.0   | 186  | 0.3653          | 0.8303   |
| No log        | 7.0   | 217  | 0.3533          | 0.8424   |
| No log        | 8.0   | 248  | 0.3500          | 0.8364   |
| No log        | 9.0   | 279  | 0.3416          | 0.8606   |
| No log        | 10.0  | 310  | 0.3546          | 0.8424   |
| No log        | 11.0  | 341  | 0.3469          | 0.8485   |
| No log        | 12.0  | 372  | 0.3511          | 0.8606   |
| No log        | 13.0  | 403  | 0.3883          | 0.8545   |
| No log        | 14.0  | 434  | 0.4090          | 0.8485   |
| No log        | 15.0  | 465  | 0.4301          | 0.8485   |
| No log        | 16.0  | 496  | 0.4415          | 0.8606   |
| 0.2667        | 17.0  | 527  | 0.4732          | 0.8545   |
| 0.2667        | 18.0  | 558  | 0.4849          | 0.8727   |
| 0.2667        | 19.0  | 589  | 0.4881          | 0.8788   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

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

BertWhyCommitOriginal
=====================


This model is a fine-tuned version of prajjwal1/bert-small on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4881
* Accuracy: 0.8788


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: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3