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
Modellquelle
- Art
- LoRA
- Dateigröße
- 330 MB
- Basismodell
- deepseek-ai/DeepSeek-OCR-2
- Version
- vRevision 82d0c14
- Aktualisiert
- 2. Okt. 2026
- Verleger
- @YUNGHUI2024
- Downloads
- 15
- Aufgaben
- Textgenerierung
- Quelle
- Hugging Face
Quellenbeschreibung
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 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
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.
- Try ML Intern: https://smolagents-ml-intern.hf.space
- Source code: https://github.com/huggingface/ml-intern
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.
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 2. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 Artefaktadapter_model.safetensors
safetensors · 330 MB · SHA-256 44a3e654cca6…af04 · Hugging Face
HerunterladenQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- 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
