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ICSR_classification_finetuned_llama_adapters_V100
DKTech/ICSR_classification_finetuned_llama_adapters_V100
ICSR_classification_finetuned_llama_adapters_V100 is a machine learning model from DKTech. 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 llama3.1.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- llama3.1
- Access
- Public
- Created
- Aug 21, 2024
- Updated
- Aug 21, 2024
- SHA
- f2f4dbb4
Base models
Datasets
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. -->
ICSR_classification_finetuned_llama_adapters_V100_test
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.2486
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3176 | 0.2915 | 500 | 1.2861 |
| 1.2716 | 0.5829 | 1000 | 1.2627 |
| 1.248 | 0.8744 | 1500 | 1.2486 |
Framework versions
- PEFT 0.11.1
- Transformers 4.44.0
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- llama3.1
- Created
- Aug 21, 2024
- Updated
- Aug 21, 2024