llama3.2-1b-instruct-fft-transduction-engineer_lr1e-5_epoch4
This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on the barc0/transduction_angmented_100k-gpt4-description-gpt4omini-code_generated_problems, the barc0/transduction_angmented_100k_gpt4o-mini_generated_problems and the barc0/transduction_rearc_dataset_400k datasets. It achieves the following results on the evaluation set:
- Loss: 0.0409
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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0618 | 1.0 | 1126 | 0.0657 |
| 0.0504 | 2.0 | 2252 | 0.0494 |
| 0.0363 | 3.0 | 3378 | 0.0418 |
| 0.0238 | 4.0 | 4504 | 0.0409 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
meta-llama/Llama-3.2-1B-Instruct