deepseek-ocr2-chart-v1

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deepseek-ocr2-chart-v1

This model is a fine-tuned version of deepseek-ai/DeepSeek-OCR-2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6978

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: 0.0002
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• 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: 0.1
• num_epochs: 10

Training results

Framework versions

• PEFT 0.19.1
• Transformers 4.46.3
• Pytorch 2.6.0+cu124
• Datasets 4.8.5
• Tokenizers 0.20.3

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Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = 'YUNGHUI2024/deepseek-ocr2-chart-v1'
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

For non-causal architectures, replace AutoModelForCausalLM with the appropriate AutoModel class.