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---
base_model: llava-hf/llava-1.5-7b-hf
library_name: peft
license: llama2
metrics:
- bleu
- rouge
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llava_test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llava_test
This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0446
- Bleu: 0.6353
- Rouge1: 0.7885
- Rouge2: 0.7889
- Rougel: 0.7893
- Bertscore Precision: 0.6807
- Bertscore Recall: 0.7674
- Bertscore F1: 0.7213
## 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: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
| 0.3168 | 10.0 | 10 | 2.2001 | 0.0724 | 0.3123 | 0.1239 | 0.2433 | 0.7068 | 0.7777 | 0.7405 |
| 0.2454 | 20.0 | 20 | 1.6882 | 0.1061 | 0.4044 | 0.1840 | 0.3274 | 0.7241 | 0.7794 | 0.7507 |
| 0.1821 | 30.0 | 30 | 1.1567 | 0.1925 | 0.5281 | 0.2989 | 0.4593 | 0.7054 | 0.7756 | 0.7387 |
| 0.109 | 40.0 | 40 | 0.5242 | 0.3915 | 0.6689 | 0.5316 | 0.6370 | 0.6878 | 0.7709 | 0.7268 |
| 0.0378 | 50.0 | 50 | 0.1193 | 0.5971 | 0.7701 | 0.7585 | 0.7700 | 0.6839 | 0.7688 | 0.7237 |
| 0.0098 | 60.0 | 60 | 0.0554 | 0.6254 | 0.7862 | 0.7867 | 0.7875 | 0.6799 | 0.7694 | 0.7217 |
| 0.0064 | 70.0 | 70 | 0.0482 | 0.6329 | 0.7889 | 0.7890 | 0.7899 | 0.6798 | 0.7690 | 0.7215 |
| 0.0059 | 80.0 | 80 | 0.0459 | 0.6331 | 0.7877 | 0.7877 | 0.7888 | 0.6777 | 0.7670 | 0.7194 |
| 0.0057 | 90.0 | 90 | 0.0451 | 0.6347 | 0.7897 | 0.7895 | 0.7907 | 0.6807 | 0.7675 | 0.7213 |
| 0.0056 | 100.0 | 100 | 0.0446 | 0.6353 | 0.7885 | 0.7889 | 0.7893 | 0.6807 | 0.7674 | 0.7213 |
### Framework versions
- PEFT 0.13.0
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.1 |