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--- |
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license: bsd-3-clause |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: blip-image-captioning-base-blip-dummy-temp-1 |
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results: [] |
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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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# blip-image-captioning-base-blip-dummy-temp-1 |
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This model is a fine-tuned version of [Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7117 |
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- Wer Score: 0.4618 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:| |
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| 7.1762 | 3.23 | 50 | 4.4355 | 0.8626 | |
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| 2.7292 | 6.45 | 100 | 1.8212 | 0.7393 | |
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| 1.6499 | 9.68 | 150 | 1.7030 | 0.5773 | |
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| 1.4923 | 12.9 | 200 | 1.6767 | 0.5157 | |
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| 1.4285 | 16.13 | 250 | 1.6746 | 0.4752 | |
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| 1.3994 | 19.35 | 300 | 1.6786 | 0.4720 | |
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| 1.3862 | 22.58 | 350 | 1.6862 | 0.4611 | |
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| 1.3801 | 25.81 | 400 | 1.6925 | 0.4572 | |
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| 1.3764 | 29.03 | 450 | 1.6972 | 0.4590 | |
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| 1.3742 | 32.26 | 500 | 1.7026 | 0.4583 | |
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| 1.3727 | 35.48 | 550 | 1.7066 | 0.4604 | |
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| 1.3718 | 38.71 | 600 | 1.7087 | 0.4600 | |
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| 1.3712 | 41.94 | 650 | 1.7102 | 0.4597 | |
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| 1.3708 | 45.16 | 700 | 1.7113 | 0.4614 | |
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| 1.3707 | 48.39 | 750 | 1.7117 | 0.4618 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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