rohitsaxena
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test

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test

This model is a fine-tuned version of llava-hf/llava-1.5-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.7232
Bleu: 0.0387
Rouge1: 0.2677
Rouge2: 0.0882
Rougel: 0.2007
Bertscore Precision: 0.6978
Bertscore Recall: 0.7745
Bertscore F1: 0.7341

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: 5e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Rouge1	Rouge2	Rougel	Bertscore Precision	Bertscore Recall	Bertscore F1
No log	0.0495	1	2.7394	0.0387	0.2665	0.0883	0.1998	0.6979	0.7743	0.7340
No log	0.0991	2	2.7232	0.0387	0.2677	0.0882	0.2007	0.6978	0.7745	0.7341

Framework versions

PEFT 0.13.0
Transformers 4.44.2
Pytorch 2.2.0a0+81ea7a4
Datasets 2.20.0
Tokenizers 0.19.1

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Evaluation results

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