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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- jmhessel/newyorker_caption_contest |
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base_model: BridgeTower/bridgetower-large-itm-mlm-itc |
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model-index: |
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- name: bridgetower-newyorker-a100-8x |
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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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# bridgetower-newyorker-a100-8x |
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> Disclaimer: Those are the results I obtained with an older version of software. It is possible to fit batches of 48 samples and to get better throughput as mentioned in this blog post: https://huggingface.co/blog/bridgetower |
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This model is a fine-tuned version of [BridgeTower/bridgetower-large-itm-mlm-itc](https://huggingface.co/BridgeTower/bridgetower-large-itm-mlm-itc) on the jmhessel/newyorker_caption_contest matching dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1148 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 128 |
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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: 5.0 |
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### Training results |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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