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--- |
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license: mit |
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base_model: microsoft/git-base |
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tags: |
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- generated_from_trainer |
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- image-to-text |
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- image-captioning |
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model-index: |
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- name: git-base-instagram-cap |
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results: [] |
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pipeline_tag: image-to-text |
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language: |
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- en |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# git-base-instagram-cap |
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2581 |
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- Wer Score: 3.1462 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:| |
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| 7.3639 | 3.45 | 50 | 4.5936 | 0.9495 | |
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| 2.389 | 6.9 | 100 | 0.6192 | 0.9387 | |
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| 0.2242 | 10.34 | 150 | 0.2274 | 0.9036 | |
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| 0.0883 | 13.79 | 200 | 0.2271 | 0.9084 | |
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| 0.0643 | 17.24 | 250 | 0.2319 | 0.9387 | |
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| 0.0493 | 20.69 | 300 | 0.2388 | 0.9501 | |
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| 0.0409 | 24.14 | 350 | 0.2435 | 0.9522 | |
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| 0.0344 | 27.59 | 400 | 0.2458 | 0.9616 | |
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| 0.0311 | 31.03 | 450 | 0.2492 | 1.0027 | |
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| 0.028 | 34.48 | 500 | 0.2519 | 1.3565 | |
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| 0.0255 | 37.93 | 550 | 0.2540 | 2.0640 | |
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| 0.0227 | 41.38 | 600 | 0.2554 | 2.1813 | |
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| 0.0189 | 44.83 | 650 | 0.2575 | 2.8416 | |
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| 0.0154 | 48.28 | 700 | 0.2581 | 3.1462 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
