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--- |
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license: llama2 |
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datasets: |
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- REILX/text-description-of-the-meme |
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language: |
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- en |
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- zh |
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tags: |
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- llava |
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- lora |
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--- |
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<style> |
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.img-responsive { |
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width: 100%; |
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height: auto; |
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} |
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</style> |
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### Conclusion |
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While significantly better at understanding and describing emotions and details in images compared to LLaVA-1.5-7b-hf, the fine-tuned model struggles with recognizing text. |
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### Train Loss |
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<img src="./adapter-module/training_loss.png" alt="loss" class="img-responsive"> |
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### Test |
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A comparative analysis of emoji in prompts, differents between the original model and its fine-tuned counterpart. </br> |
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Original Model:https://huggingface.co/llava-hf/llava-1.5-7b-hf/</br> |
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<img src="./images/original-01.JPG" alt="meme01" class="img-responsive"> |
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<img src="./images/original-02.JPG" alt="meme02" class="img-responsive"> |
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<img src="./images/original-03.JPG" alt="meme03" class="img-responsive"> |
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Fine-tuned Lora Model:https://huggingface.co/REILX/llava-1.5-7b-hf-meme-lora</br> |
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<img src="./images/lora-01.JPG" alt="meme01" class="img-responsive"> |
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<img src="./images/lora-02.JPG" alt="meme02" class="img-responsive"> |
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<img src="./images/lora-03.JPG" alt="meme03" class="img-responsive"> |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- cutoff_len: 2048 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 8 |
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- total_eval_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: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 5.0 |
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