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gemma-2-9b-4bit-vi-sentence-simplification-adapter
Tung177/gemma-2-9b-4bit-vi-sentence-simplification-adapter
gemma-2-9b-4bit-vi-sentence-simplification-adapter is a machine learning model from Tung177. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- Oct 14, 2024
- Updated
- Oct 14, 2024
- SHA
- d5f87ee1
Base models
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. -->
gemma-2-9b-lr7.5e-05e1r256dr0
This model is a fine-tuned version of google/gemma-2-9b on the ss-train 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: 7.5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_min_lr
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Library
- peft
- License
- other
- Created
- Oct 14, 2024
- Updated
- Oct 14, 2024