metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_60-samples_config-1
results: []
Llama-31-8B_task-1_60-samples_config-1
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.7460
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_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: 50
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.1529 | 0.8696 | 5 | 2.0041 |
1.7276 | 1.9130 | 11 | 1.6163 |
1.5018 | 2.9565 | 17 | 1.4631 |
1.3727 | 4.0 | 23 | 1.3338 |
1.0912 | 4.8696 | 28 | 1.2853 |
0.8709 | 5.9130 | 34 | 1.2905 |
0.713 | 6.9565 | 40 | 1.4713 |
0.4007 | 8.0 | 46 | 1.6719 |
0.2182 | 8.8696 | 51 | 2.0390 |
0.0802 | 9.9130 | 57 | 2.5003 |
0.0304 | 10.9565 | 63 | 2.7328 |
0.0155 | 12.0 | 69 | 2.7460 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1