Transformers
Safetensors
lora_run_rounded_noimg_20250404_162108
20250404_162108
lora-finetuning
lora_run_rounded_noimg_20250404_160637
20250404_160637
lora_run_rounded_noimg_20250404_160306
20250404_160306
lora_run_rounded_noimg_20250404_160131
20250404_160131
lora_run_rounded_noimg_20250404_155922
20250404_155922
lora_run_rounded_noimg_20250404_155517
20250404_155517
lora_run_rounded_noimg_20250404_154242
20250404_154242
lora_run_rounded_noimg_20250404_154200
20250404_154200
lora_run_edgelabelled_colored_20250404_141612
20250404_141612
lora_run_edgelabelled_colored_20250404_134651
20250404_134651
lora_run_rounded_colored_20250403_214449
20250403_214449
lora_run_rounded_colored_20250403_195038
20250403_195038
lora_run_rounded_colored_20250403_194012
20250403_194012
lora_run_rounded_colored_20250403_135921
20250403_135921
lora_run_rounded_colored_20250403_121200
20250403_121200
lora_run_rounded_colored_20250403_103814
20250403_103814
lora_run_rounded_colored_20250403_090510
20250403_090510
lora_run_rounded_colored_20250403_073345
20250403_073345
lora_run_rounded_colored_20250402_234837
20250402_234837
lora_run_rounded_colored_20250402_231331
20250402_231331
lora_run_rounded_colored_20250402_205929
20250402_205929
lora_run_rounded_colored_20250402_205628
20250402_205628
Generated from Trainer
lora_run_rounded_colored_20250402_204950
20250402_204950
final-model
processor
checkpoints
This model is a fine-tuned version of meta-llama/Llama-3.2-11B-Vision-Instruct on the None dataset.
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
Inference Providers
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Model tree for diliash/emuLM-spt-noimg-rounded
Base model
meta-llama/Llama-3.2-11B-Vision-Instruct