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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: 0.0350
- Wer Score: 2.2148

## 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: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3616        | 4.17  | 50   | 4.5895          | 21.4258   |
| 2.4353        | 8.33  | 100  | 0.4961          | 9.9322    |
| 0.1527        | 12.5  | 150  | 0.0303          | 1.3197    |
| 0.0192        | 16.67 | 200  | 0.0260          | 1.3299    |
| 0.007         | 20.83 | 250  | 0.0297          | 2.2059    |
| 0.0027        | 25.0  | 300  | 0.0321          | 2.4795    |
| 0.0017        | 29.17 | 350  | 0.0334          | 2.4488    |
| 0.0014        | 33.33 | 400  | 0.0340          | 2.1355    |
| 0.0013        | 37.5  | 450  | 0.0345          | 2.3619    |
| 0.0012        | 41.67 | 500  | 0.0349          | 2.2084    |
| 0.0011        | 45.83 | 550  | 0.0350          | 2.1803    |
| 0.0011        | 50.0  | 600  | 0.0350          | 2.2148    |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
{"license": "mit", "tags": ["generated_from_trainer", "image-to-text"], "datasets": ["imagefolder"], "pipeline_tag": "image-to-text", "model-index": [{"name": "git-base-pokemon", "results": []}]}
transformers pytorch safetensors git text-generation generated_from_trainer image-to-text dataset:imagefolder license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #git #text-generation #generated_from_trainer #image-to-text #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: 0.0350
* Wer Score: 2.2148


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: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* 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 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* 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: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* 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 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #git #text-generation #generated_from_trainer #image-to-text #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: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* 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 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2