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---
library_name: transformers
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: git-base-one-entrance-dungeons-20
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# git-base-one-entrance-dungeons-20
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: 0.0115
- Wer Score: 0.2812
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 0.0112 | 0.6061 | 10 | 0.0108 | 0.2812 |
| 0.0094 | 1.2121 | 20 | 0.0105 | 0.25 |
| 0.0109 | 1.8182 | 30 | 0.0114 | 0.2656 |
| 0.0112 | 2.4242 | 40 | 0.0103 | 0.25 |
| 0.0114 | 3.0303 | 50 | 0.0108 | 0.2812 |
| 0.0107 | 3.6364 | 60 | 0.0113 | 0.2812 |
| 0.0119 | 4.2424 | 70 | 0.0108 | 0.2344 |
| 0.0121 | 4.8485 | 80 | 0.0106 | 0.2344 |
| 0.0115 | 5.4545 | 90 | 0.0112 | 0.25 |
| 0.0126 | 6.0606 | 100 | 0.0107 | 0.25 |
| 0.0118 | 6.6667 | 110 | 0.0119 | 0.25 |
| 0.0116 | 7.2727 | 120 | 0.0105 | 0.2188 |
| 0.0122 | 7.8788 | 130 | 0.0105 | 0.2656 |
| 0.0103 | 8.4848 | 140 | 0.0109 | 0.2812 |
| 0.0102 | 9.0909 | 150 | 0.0107 | 0.25 |
| 0.0099 | 9.6970 | 160 | 0.0118 | 0.25 |
| 0.0091 | 10.3030 | 170 | 0.0113 | 0.2656 |
| 0.0095 | 10.9091 | 180 | 0.0109 | 0.2656 |
| 0.0093 | 11.5152 | 190 | 0.0114 | 0.25 |
| 0.0088 | 12.1212 | 200 | 0.0119 | 0.2812 |
| 0.0091 | 12.7273 | 210 | 0.0123 | 0.2812 |
| 0.009 | 13.3333 | 220 | 0.0119 | 0.2969 |
| 0.0092 | 13.9394 | 230 | 0.0112 | 0.25 |
| 0.0084 | 14.5455 | 240 | 0.0116 | 0.2812 |
| 0.009 | 15.1515 | 250 | 0.0118 | 0.2969 |
| 0.0077 | 15.7576 | 260 | 0.0120 | 0.2656 |
| 0.008 | 16.3636 | 270 | 0.0116 | 0.2344 |
| 0.0079 | 16.9697 | 280 | 0.0115 | 0.2812 |
| 0.0077 | 17.5758 | 290 | 0.0115 | 0.2812 |
| 0.0079 | 18.1818 | 300 | 0.0116 | 0.2812 |
| 0.0084 | 18.7879 | 310 | 0.0115 | 0.2812 |
| 0.0085 | 19.3939 | 320 | 0.0115 | 0.2812 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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