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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llava-hf/llava-1.5-7b-hf