|
--- |
|
library_name: transformers |
|
license: other |
|
base_model: llava-hf/llava-v1.6-mistral-7b-hf |
|
tags: |
|
- llama-factory |
|
- full |
|
- generated_from_trainer |
|
model-index: |
|
- name: Compcap_cooccur_0_50 |
|
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. --> |
|
|
|
# Compcap_cooccur_0_50 |
|
|
|
This model is a fine-tuned version of [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) on the Compcap_cooccur_0_50 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8218 |
|
|
|
## 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-06 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 256 |
|
- total_eval_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 10 |
|
- num_epochs: 3.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.9274 | 0.2706 | 50 | 0.9372 | |
|
| 0.8893 | 0.5413 | 100 | 0.8818 | |
|
| 0.8684 | 0.8119 | 150 | 0.8576 | |
|
| 0.7885 | 1.0825 | 200 | 0.8444 | |
|
| 0.7588 | 1.3532 | 250 | 0.8343 | |
|
| 0.7736 | 1.6238 | 300 | 0.8263 | |
|
| 0.7499 | 1.8945 | 350 | 0.8208 | |
|
| 0.6949 | 2.1651 | 400 | 0.8236 | |
|
| 0.7056 | 2.4357 | 450 | 0.8227 | |
|
| 0.7001 | 2.7064 | 500 | 0.8219 | |
|
| 0.7045 | 2.9770 | 550 | 0.8218 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.20.3 |
|
|
