End of training
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README.md
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---
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library_name: transformers
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license: bsd-3-clause
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base_model: Salesforce/blip-image-captioning-large
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: blip-image-captioning-large-shyam
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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-large-shyam
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This model is a fine-tuned version of [Salesforce/blip-image-captioning-large](https://huggingface.co/Salesforce/blip-image-captioning-large) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0217
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- Wer Score: 0.25
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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: 2
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- eval_batch_size: 2
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 15
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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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| 6.6439 | 3.5714 | 50 | 3.4493 | 0.5833 |
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| 1.4414 | 7.1429 | 100 | 0.2345 | 0.375 |
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| 0.0696 | 10.7143 | 150 | 0.0300 | 0.375 |
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| 0.0089 | 14.2857 | 200 | 0.0217 | 0.25 |
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### Framework versions
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- Transformers 4.46.0.dev0
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 30522,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.46.0.dev0"
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}
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runs/Oct01_20-35-32_3338b107fa91/events.out.tfevents.1727814934.3338b107fa91.506.0
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size
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size 7684
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