---
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_60
  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_cosi_0_60

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_cosi_0_60 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8026

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9416        | 0.2257 | 50   | 0.9273          |
| 0.876         | 0.4515 | 100  | 0.8720          |
| 0.8328        | 0.6772 | 150  | 0.8474          |
| 0.8288        | 0.9029 | 200  | 0.8303          |
| 0.772         | 1.1287 | 250  | 0.8230          |
| 0.7434        | 1.3544 | 300  | 0.8150          |
| 0.7387        | 1.5801 | 350  | 0.8084          |
| 0.7409        | 1.8059 | 400  | 0.8031          |
| 0.7112        | 2.0316 | 450  | 0.8033          |
| 0.7123        | 2.2573 | 500  | 0.8042          |
| 0.7057        | 2.4831 | 550  | 0.8041          |
| 0.6976        | 2.7088 | 600  | 0.8029          |
| 0.6986        | 2.9345 | 650  | 0.8026          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3