Aller au contenu
ModelVérifiéExterne
Télécharger

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

TypeLoRAModèle de basedeepseek-ai/DeepSeek-OCR-2VersionRevision 82d0c14Éditeur@YUNGHUI2024CClasse

Source du modèle

Type
LoRA
Taille du fichier
330 MB
Modèle de base
deepseek-ai/DeepSeek-OCR-2
Version
vRevision 82d0c14
Mis à jour
2 oct. 2026
Éditeur
@YUNGHUI2024
Téléchargements
15
Tâches
Génération de texte
Source
Hugging Face

Description de la source

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

Training LossEpochStepValidation Loss
1.37690.571411.2913
1.37691.714330.9567
0.97142.857150.7840
0.97144.070.7222
0.97144.571480.7006
0.59745.7143100.6978

Framework versions

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

Generated by ML Intern

This model repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.

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.

Sources

1 source
Hugging FacePrincipalVersion 82d0c1444b043549aacfff62797b61e4175f6769
huggingface.co/YUNGHUI2024/deepseek-ocr2-chart-v1/tree/82d0c1444b043549aacfff62797b61e4175f6769

Vérifié 2 oct.

Artefacts du modèle

1 artefact

adapter_model.safetensors

safetensors · 330 MB · SHA-256 44a3e654cca6…af04 · Hugging Face

Télécharger

Extraits de sources

3 extraits

--- library_name: peft license: apache-2.0 base_model: deepseek-ai/DeepSeek-OCR-2 tags: - base_model:adapter:deepseek-ai/DeepSeek-OCR-2 - lora - transformers - ml-intern pipeline_tag: text-generation model-index: - name: deepseek-ocr2-chart-v1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # deepseek-ocr2-chart-v1 This model is a fine-tuned version of [deepseek-ai/DeepSeek-OCR-2](https://huggingface.co/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 | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.3769 | 0.5714 | 1 | 1.2913 | | 1.3769 | 1.7143 | 3 | 0.9567 | | 0.9714 | 2.8571 | 5 | 0.7840 | | 0.9714 | 4.0 | 7 | 0.7222 | | 0.9714 | 4.5714 | 8 | 0.7006 | | 0.5974 | 5.7143 | 10 | 0.6978 | ### Framework versions - PEFT 0.19.1 - Transformers 4.46.3 - Pytorch 2.6.0+cu124 - Datasets 4.8.5 - Tokenizers 0.20.3 <!-- ml-intern-provenance --> ## Generated by ML Intern This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub. - Try ML Intern: https://smolagents-ml-intern.hf.space - Source code: https://github.com/huggingface/ml-intern ## Usage ```python 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 `AutoModelFor...

Source context: 15 downloads · 0 likes · Pipeline text-generation · Library peft · Repo YUNGHUI2024/deepseek-ocr2-chart-v1

Source context: 3 downloads · 0 likes · Pipeline text-generation · Library peft · Repo YUNGHUI2024/deepseek-ocr2-chart-v1