llama_3_alpaca_helpful
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8488
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: 2
- 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
- training_steps: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6674 | 0.7692 | 5 | 1.2667 |
| 1.0477 | 1.5385 | 10 | 1.0342 |
| 0.9043 | 2.3077 | 15 | 0.9358 |
| 0.8856 | 3.0769 | 20 | 0.8651 |
| 0.7671 | 3.8462 | 25 | 0.8490 |
| 0.7132 | 4.6154 | 30 | 0.8488 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Downloads last month
- 3
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
HF Inference API was unable to determine this model’s pipeline type.
Model tree for CharlesLi/llama_3_alpaca_helpful
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct