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sdar_4b_opencodeinstruct-dynamic-10epochSansa__mix_BackwardAveraged_0129_0640
armanakbari4/sdar_4b_opencodeinstruct-dynamic-10epochSansa__mix_BackwardAveraged_0129_0640
sdar_4b_opencodeinstruct-dynamic-10epochSansa__mix_BackwardAveraged_0129_0640 is a feature extraction model from armanakbari4. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- License
- other
- Model type
- sdar
- Access
- Public
- Created
- Feb 5, 2026
- Updated
- Feb 5, 2026
- SHA
- 710cb559
Model card
From the Hugging Face model README
<!-- 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. -->
sdar_4b_opencodeinstruct-dynamic-10epochSansa__mix_BackwardAveraged_['opencodeinstruct_eob']_block_None_0129_0640
This model is a fine-tuned version of training/model/SDAR-4B-Chat-mix on the opencodeinstruct_eob dataset.
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: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 2048
- total_eval_batch_size: 64
- 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: 0.03
- num_epochs: 4
Training results
Framework versions
- Transformers 4.52.4
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Feature Extraction
- Library
- transformers
- Type
- sdar
- License
- other
- Created
- Feb 5, 2026
- Updated
- Feb 5, 2026