LORA file for transduction test time finetune
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engineer1-heavy-barc-llama3.1-8b-instruct-lora64-testtime-finetuning
This model is a fine-tuned version of barc0/engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3 on the barc0/transduction_augmented_test_timearc_all_evaluation_new_seperate, the barc0/transduction_rearc_dataset_400k and the barc0/transduction_heavy_100k_jsonl datasets. It achieves the following results on the evaluation set:
- Loss: 0.0333
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: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0331 | 1.0 | 1334 | 0.0359 |
| 0.028 | 2.0 | 2668 | 0.0299 |
| 0.0009 | 3.0 | 4002 | 0.0333 |
Framework versions
- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for barc0/Llama-3.1-ARC-Potpourri-Transduction-8B-test-time-finetune
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct