---
license: mit
tags:
- generated_from_trainer
datasets:
- jmhessel/newyorker_caption_contest
model-index:
- name: bridgetower-newyorker-gaudi2-8x
  results: []
---

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# bridgetower-newyorker-gaudi2-8x

> Disclaimer: Those are the results I obtained with an older version of Optimum Habana. With v1.7, 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

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.
It achieves the following results on the evaluation set:
- Loss: 0.1147
- Memory Allocated (gb): 20.01
- Max Memory Allocated (gb): 83.39
- Total Memory Available (gb): 93.74

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 40
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 320
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1a0+git37b7ddc
- Datasets 2.13.1
- Tokenizers 0.13.3