# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText
processor = AutoProcessor.from_pretrained("Falah/git-base-ante2024")
model = AutoModelForImageTextToText.from_pretrained("Falah/git-base-ante2024")Quick Links
git-base-ante2024
This model is a fine-tuned version of microsoft/git-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.8122
- Wer Score: 3.0415
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 |
|---|---|---|---|---|
| 7.184 | 20.0 | 50 | 5.2098 | 3.5253 |
| 4.3031 | 40.0 | 100 | 3.8122 | 3.0415 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.9.0
- Tokenizers 0.15.0
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Model tree for Falah/git-base-ante2024
Base model
microsoft/git-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Falah/git-base-ante2024")