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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: 0.0429
- Wer Score: 1.9591

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3666        | 1.06  | 50   | 4.4430          | 21.5287   |
| 2.1581        | 2.13  | 100  | 0.2911          | 0.9783    |
| 0.0896        | 3.19  | 150  | 0.0328          | 0.3665    |
| 0.0269        | 4.26  | 200  | 0.0274          | 0.3487    |
| 0.0208        | 5.32  | 250  | 0.0284          | 0.4189    |
| 0.0168        | 6.38  | 300  | 0.0287          | 1.1673    |
| 0.0133        | 7.45  | 350  | 0.0296          | 6.0881    |
| 0.0106        | 8.51  | 400  | 0.0306          | 1.7969    |
| 0.0076        | 9.57  | 450  | 0.0322          | 7.1852    |
| 0.0053        | 10.64 | 500  | 0.0329          | 14.8889   |
| 0.0039        | 11.7  | 550  | 0.0338          | 12.2720   |
| 0.0027        | 12.77 | 600  | 0.0356          | 5.1533    |
| 0.0016        | 13.83 | 650  | 0.0371          | 8.4253    |
| 0.001         | 14.89 | 700  | 0.0379          | 6.7344    |
| 0.0006        | 15.96 | 750  | 0.0385          | 7.7586    |
| 0.0005        | 17.02 | 800  | 0.0392          | 9.0294    |
| 0.0004        | 18.09 | 850  | 0.0385          | 7.5083    |
| 0.0004        | 19.15 | 900  | 0.0394          | 5.1188    |
| 0.0004        | 20.21 | 950  | 0.0397          | 5.0600    |
| 0.0004        | 21.28 | 1000 | 0.0399          | 4.4125    |
| 0.0003        | 22.34 | 1050 | 0.0405          | 3.7803    |
| 0.0003        | 23.4  | 1100 | 0.0406          | 3.3397    |
| 0.0003        | 24.47 | 1150 | 0.0408          | 3.3218    |
| 0.0003        | 25.53 | 1200 | 0.0411          | 2.8212    |
| 0.0003        | 26.6  | 1250 | 0.0411          | 2.7165    |
| 0.0003        | 27.66 | 1300 | 0.0414          | 2.7625    |
| 0.0003        | 28.72 | 1350 | 0.0416          | 2.4330    |
| 0.0003        | 29.79 | 1400 | 0.0416          | 2.2350    |
| 0.0003        | 30.85 | 1450 | 0.0419          | 2.1699    |
| 0.0003        | 31.91 | 1500 | 0.0421          | 2.0026    |
| 0.0003        | 32.98 | 1550 | 0.0420          | 2.1609    |
| 0.0003        | 34.04 | 1600 | 0.0421          | 2.0307    |
| 0.0003        | 35.11 | 1650 | 0.0422          | 1.9668    |
| 0.0003        | 36.17 | 1700 | 0.0423          | 1.9387    |
| 0.0003        | 37.23 | 1750 | 0.0425          | 1.9464    |
| 0.0003        | 38.3  | 1800 | 0.0427          | 1.8761    |
| 0.0003        | 39.36 | 1850 | 0.0427          | 1.8940    |
| 0.0003        | 40.43 | 1900 | 0.0428          | 1.9068    |
| 0.0003        | 41.49 | 1950 | 0.0428          | 1.8774    |
| 0.0003        | 42.55 | 2000 | 0.0429          | 1.8352    |
| 0.0002        | 43.62 | 2050 | 0.0428          | 2.0907    |
| 0.0002        | 44.68 | 2100 | 0.0429          | 2.0319    |
| 0.0002        | 45.74 | 2150 | 0.0429          | 2.0179    |
| 0.0002        | 46.81 | 2200 | 0.0429          | 1.9706    |
| 0.0002        | 47.87 | 2250 | 0.0429          | 1.9604    |
| 0.0002        | 48.94 | 2300 | 0.0429          | 1.9540    |
| 0.0002        | 50.0  | 2350 | 0.0429          | 1.9591    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "model-index": [{"name": "git-base-pokemon", "results": []}]}
transformers pytorch tensorboard git text-generation generated_from_trainer dataset:imagefolder license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #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: 0.0429
* Wer Score: 1.9591


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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3