potpourri-testtime-finetuning-100_test_aug100
This model is a fine-tuned version of barc0/Llama-3.1-ARC-Potpourri-Transduction-8B on the barc0/100_subset_test_aug_100 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0128
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|---|---|---|---|
| 0.0168 | 0.9989 | 451 | 0.0255 |
| 0.0092 | 2.0 | 903 | 0.0133 |
| 0.0019 | 2.9967 | 1353 | 0.0128 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Model tree for barc0/potpourri-testtime-finetuning-100_test_aug100
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct