This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the Align-Anything-L0-q0_25 dataset. It achieves the following results on the evaluation set:

Loss: 0.8606

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
0.9473	0.5731	50	0.9285
0.7919	1.1461	100	0.8879
0.7632	1.7192	150	0.8642
0.685	2.2923	200	0.8616
0.6852	2.8653	250	0.8607

Framework versions

Transformers 4.45.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.20.3

htlou/backup_0202_llamafactory_Align-Anything-L0-q0_25-llava-mistral

Align-Anything-L0-q0_25

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

htlou/
backup_0202_llamafactory_Align-Anything-L0-q0_25-llava-mistral