sft-llava-1.5-7b_new
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: 1.9504
- Bleu: 0.1425
- Rouge1: 0.4583
- Rouge2: 0.1850
- Rougel: 0.3579
- Bertscore Precision: 0.6782
- Bertscore Recall: 0.7679
- Bertscore F1: 0.7201
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|---|---|---|---|---|---|---|---|---|---|---|
| 1.9977 | 0.9922 | 80 | 1.9963 | 0.1395 | 0.4530 | 0.1844 | 0.3520 | 0.6764 | 0.7670 | 0.7188 |
| 1.9336 | 1.9845 | 160 | 1.9504 | 0.1425 | 0.4583 | 0.1850 | 0.3579 | 0.6782 | 0.7679 | 0.7201 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.1
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Model tree for rohitsaxena/sft-llava-1.5-7b_new
Base model
llava-hf/llava-1.5-7b-hf