metadata
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_cosi_0_40
results: []
Compcap_cosi_0_40
This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the Compcap_cosi_0_40 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8345
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 |
|---|---|---|---|
| 0.9333 | 0.3384 | 50 | 0.9388 |
| 0.8736 | 0.6768 | 100 | 0.8821 |
| 0.8459 | 1.0152 | 150 | 0.8576 |
| 0.7682 | 1.3536 | 200 | 0.8485 |
| 0.7797 | 1.6920 | 250 | 0.8385 |
| 0.7246 | 2.0305 | 300 | 0.8337 |
| 0.7082 | 2.3689 | 350 | 0.8360 |
| 0.7007 | 2.7073 | 400 | 0.8346 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3