AlexHung29629

gemma-4-E2B-sft-stage2-vision

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README

License: apache-2.0

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-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 64
total_eval_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_8BIT with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 5
training_steps: 185

Training results

Table with columns: Training Loss, Epoch, Step, Validation Loss, Ppl, Active (gib), Allocated (gib), Reserved (gib)
Training Loss	Epoch	Step	Validation Loss	Ppl	Active (gib)	Allocated (gib)	Reserved (gib)
No log	0	0	2.5641	12.9889	19.57	19.57	19.8
1.6469	1.0	10	1.7048

Framework versions

Transformers 5.14.1
Pytorch 2.11.0
Datasets 4.8.4
Tokenizers 0.22.2

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Model Details

Model Provider

AlexHung29629

Model Tree

Base

AlexHung29629/gemma-4-E2B-sft-stage1-embed

Fine-tuned

this model

Input Modalities

TextImage

Output Modalities

Text

Supported Functionality

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README

License: apache-2.0

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-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 64
total_eval_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_8BIT with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 5
training_steps: 185

Training results

Table with columns: Training Loss, Epoch, Step, Validation Loss, Ppl, Active (gib), Allocated (gib), Reserved (gib)
Training Loss	Epoch	Step	Validation Loss	Ppl	Active (gib)	Allocated (gib)	Reserved (gib)
No log	0	0	2.5641	12.9889	19.57	19.57	19.8
1.6469	1.0	10	1.7048

Framework versions

Transformers 5.14.1
Pytorch 2.11.0
Datasets 4.8.4
Tokenizers 0.22.2