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# git-base-pokemon

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0396
- Wer Score: 6.0488

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3484        | 1.06  | 50   | 4.4320          | 10.6547   |
| 2.1536        | 2.13  | 100  | 0.2910          | 1.8947    |
| 0.0909        | 3.19  | 150  | 0.0322          | 0.3684    |
| 0.0278        | 4.26  | 200  | 0.0275          | 0.3659    |
| 0.0211        | 5.32  | 250  | 0.0271          | 0.8858    |
| 0.0185        | 6.38  | 300  | 0.0267          | 0.6778    |
| 0.0155        | 7.45  | 350  | 0.0272          | 7.8190    |
| 0.0129        | 8.51  | 400  | 0.0279          | 3.2452    |
| 0.0108        | 9.57  | 450  | 0.0280          | 15.0462   |
| 0.0082        | 10.64 | 500  | 0.0291          | 10.0372   |
| 0.0069        | 11.7  | 550  | 0.0303          | 15.1592   |
| 0.0048        | 12.77 | 600  | 0.0321          | 15.4493   |
| 0.0033        | 13.83 | 650  | 0.0322          | 16.2439   |
| 0.0022        | 14.89 | 700  | 0.0350          | 17.7125   |
| 0.0017        | 15.96 | 750  | 0.0340          | 16.8357   |
| 0.0011        | 17.02 | 800  | 0.0354          | 16.8780   |
| 0.0009        | 18.09 | 850  | 0.0351          | 17.3273   |
| 0.0006        | 19.15 | 900  | 0.0364          | 16.4788   |
| 0.0005        | 20.21 | 950  | 0.0368          | 15.4442   |
| 0.0004        | 21.28 | 1000 | 0.0368          | 16.2336   |
| 0.0004        | 22.34 | 1050 | 0.0375          | 14.1168   |
| 0.0004        | 23.4  | 1100 | 0.0375          | 14.4365   |
| 0.0004        | 24.47 | 1150 | 0.0373          | 12.3890   |
| 0.0004        | 25.53 | 1200 | 0.0379          | 8.7843    |
| 0.0004        | 26.6  | 1250 | 0.0382          | 9.2298    |
| 0.0003        | 27.66 | 1300 | 0.0383          | 8.8562    |
| 0.0003        | 28.72 | 1350 | 0.0384          | 9.5777    |
| 0.0003        | 29.79 | 1400 | 0.0383          | 8.6021    |
| 0.0003        | 30.85 | 1450 | 0.0387          | 7.9782    |
| 0.0003        | 31.91 | 1500 | 0.0387          | 7.7394    |
| 0.0003        | 32.98 | 1550 | 0.0388          | 7.6431    |
| 0.0003        | 34.04 | 1600 | 0.0389          | 6.9037    |
| 0.0003        | 35.11 | 1650 | 0.0391          | 6.8665    |
| 0.0003        | 36.17 | 1700 | 0.0392          | 6.0526    |
| 0.0003        | 37.23 | 1750 | 0.0394          | 5.6996    |
| 0.0003        | 38.3  | 1800 | 0.0393          | 6.1361    |
| 0.0003        | 39.36 | 1850 | 0.0394          | 5.9127    |
| 0.0003        | 40.43 | 1900 | 0.0394          | 5.6816    |
| 0.0003        | 41.49 | 1950 | 0.0394          | 5.3723    |
| 0.0003        | 42.55 | 2000 | 0.0395          | 4.8806    |
| 0.0002        | 43.62 | 2050 | 0.0395          | 6.9178    |
| 0.0002        | 44.68 | 2100 | 0.0395          | 6.2953    |
| 0.0002        | 45.74 | 2150 | 0.0395          | 6.1142    |
| 0.0002        | 46.81 | 2200 | 0.0396          | 6.0642    |
| 0.0002        | 47.87 | 2250 | 0.0396          | 6.0077    |
| 0.0002        | 48.94 | 2300 | 0.0396          | 6.0026    |
| 0.0002        | 50.0  | 2350 | 0.0396          | 6.0488    |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "model-index": [{"name": "git-base-pokemon", "results": []}]}
transformers pytorch git text-generation generated_from_trainer dataset:imagefolder license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #git #text-generation #generated_from_trainer #dataset-imagefolder #license-mit #autotrain_compatible #endpoints_compatible #region-us 

git-base-pokemon
================


This model is a fine-tuned version of microsoft/git-base on the imagefolder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0396
* Wer Score: 6.0488


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #git #text-generation #generated_from_trainer #dataset-imagefolder #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3