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smoke_test_glm4v_checkpoints – AI Model by prthm29 | AlphaNeural AI
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prthm29
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smoke_test_glm4v_checkpoints
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peft
tensorboard
safetensors
adapter
llama-factory
lora
transformers
text-generation
conversational
zai-org/GLM-OCR
mit
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smoke_test_glm4v_checkpoints
This model is a fine-tuned version of
zai-org/GLM-OCR
on the gujarati_ocr_stream dataset. It achieves the following results on the evaluation set:
Loss: 2.5668
Accuracy: 0.5594
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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1
training_steps: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.7841
0.6154
2
2.7496
0.5348
2.6433
1.0
4
2.5868
0.5556
Framework versions
PEFT 0.18.1
Transformers 5.2.0
Pytorch 2.11.0+cu130
Datasets 4.0.0
Tokenizers 0.22.2
