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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-finetuned-25epoch-1e-4 |
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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-finetuned-25epoch-1e-4 |
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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: 1.5782 |
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- Wer Score: 0.3254 |
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- Blue Score: 0.6634 |
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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: 0.0001 |
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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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Score | Blue Score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:----------:| |
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| 6.8732 | 1.01 | 35 | 3.2765 | 0.9105 | 0.0244 | |
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| 2.1287 | 2.03 | 70 | 1.7647 | 0.7923 | 0.1135 | |
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| 1.719 | 3.04 | 105 | 1.6799 | 0.6832 | 0.2382 | |
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| 1.6093 | 4.06 | 140 | 1.6328 | 0.5892 | 0.3339 | |
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| 1.5421 | 5.07 | 175 | 1.6058 | 0.5249 | 0.4004 | |
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| 1.4871 | 6.09 | 210 | 1.5880 | 0.4492 | 0.5001 | |
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| 1.4519 | 7.1 | 245 | 1.5773 | 0.4079 | 0.5568 | |
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| 1.4275 | 8.12 | 280 | 1.5694 | 0.3794 | 0.5908 | |
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| 1.4115 | 9.13 | 315 | 1.5696 | 0.3692 | 0.6075 | |
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| 1.3992 | 10.14 | 350 | 1.5649 | 0.3477 | 0.6326 | |
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| 1.3895 | 11.16 | 385 | 1.5662 | 0.3437 | 0.6424 | |
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| 1.3843 | 12.17 | 420 | 1.5694 | 0.3430 | 0.6402 | |
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| 1.3793 | 13.19 | 455 | 1.5692 | 0.3336 | 0.6553 | |
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| 1.3764 | 14.2 | 490 | 1.5710 | 0.3288 | 0.6571 | |
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| 1.3743 | 15.22 | 525 | 1.5711 | 0.3280 | 0.6631 | |
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| 1.373 | 16.23 | 560 | 1.5724 | 0.3269 | 0.6617 | |
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| 1.3715 | 17.25 | 595 | 1.5736 | 0.3241 | 0.6654 | |
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| 1.3704 | 18.26 | 630 | 1.5752 | 0.3271 | 0.6618 | |
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| 1.37 | 19.28 | 665 | 1.5758 | 0.3258 | 0.6629 | |
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| 1.3694 | 20.29 | 700 | 1.5768 | 0.3264 | 0.6627 | |
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| 1.3687 | 21.3 | 735 | 1.5767 | 0.3258 | 0.6640 | |
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| 1.3689 | 22.32 | 770 | 1.5775 | 0.3250 | 0.6636 | |
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| 1.3684 | 23.33 | 805 | 1.5780 | 0.3258 | 0.6636 | |
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| 1.3682 | 24.35 | 840 | 1.5782 | 0.3254 | 0.6634 | |
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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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