|
--- |
|
license: other |
|
base_model: meta-llama/Meta-Llama-3-8B |
|
tags: |
|
- llama-factory |
|
- full |
|
- generated_from_trainer |
|
model-index: |
|
- name: C013_llama3-8b-base_instruct_20240428_005832 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# C013_llama3-8b-base_instruct_20240428_005832 |
|
|
|
This model is a fine-tuned version of [./output/training_results/C013_llama3-8b-base_pretrain_20240428_005832/](https://huggingface.co/./output/training_results/C013_llama3-8b-base_pretrain_20240428_005832/) on the instructions_curated dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8123 |
|
|
|
## 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: 1.5e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- total_train_batch_size: 64 |
|
- total_eval_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: polynomial |
|
- lr_scheduler_warmup_steps: 20 |
|
- num_epochs: 4.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.9805 | 0.0208 | 1 | 0.9737 | |
|
| 0.9446 | 0.1042 | 5 | 0.9455 | |
|
| 0.8481 | 0.2083 | 10 | 0.8154 | |
|
| 0.7794 | 0.3125 | 15 | 0.8123 | |
|
| 0.7798 | 0.4167 | 20 | 0.8411 | |
|
| 0.8576 | 0.5208 | 25 | 0.8676 | |
|
| 0.8852 | 0.625 | 30 | 0.8673 | |
|
| 0.8529 | 0.7292 | 35 | 0.8561 | |
|
| 0.8224 | 0.8333 | 40 | 0.8470 | |
|
| 0.8536 | 0.9375 | 45 | 0.8378 | |
|
| 0.662 | 1.0417 | 50 | 0.8294 | |
|
| 0.437 | 1.1458 | 55 | 0.8531 | |
|
| 0.4402 | 1.25 | 60 | 0.8569 | |
|
| 0.4244 | 1.3542 | 65 | 0.8569 | |
|
| 0.4495 | 1.4583 | 70 | 0.8547 | |
|
| 0.4689 | 1.5625 | 75 | 0.8494 | |
|
| 0.4309 | 1.6667 | 80 | 0.8461 | |
|
| 0.4299 | 1.7708 | 85 | 0.8446 | |
|
| 0.4461 | 1.875 | 90 | 0.8440 | |
|
| 0.4474 | 1.9792 | 95 | 0.8439 | |
|
| 0.3614 | 2.0833 | 100 | 0.8445 | |
|
| 0.3861 | 2.1875 | 105 | 0.8457 | |
|
| 0.3829 | 2.2917 | 110 | 0.8473 | |
|
| 0.3764 | 2.3958 | 115 | 0.8488 | |
|
| 0.3655 | 2.5 | 120 | 0.8500 | |
|
| 0.4243 | 2.6042 | 125 | 0.8511 | |
|
| 0.3884 | 2.7083 | 130 | 0.8520 | |
|
| 0.3634 | 2.8125 | 135 | 0.8528 | |
|
| 0.3846 | 2.9167 | 140 | 0.8537 | |
|
| 0.3872 | 3.0208 | 145 | 0.8547 | |
|
| 0.3869 | 3.125 | 150 | 0.8558 | |
|
| 0.3876 | 3.2292 | 155 | 0.8566 | |
|
| 0.3844 | 3.3333 | 160 | 0.8573 | |
|
| 0.3535 | 3.4375 | 165 | 0.8579 | |
|
| 0.3488 | 3.5417 | 170 | 0.8588 | |
|
| 0.3464 | 3.6458 | 175 | 0.8598 | |
|
| 0.361 | 3.75 | 180 | 0.8607 | |
|
| 0.3674 | 3.8542 | 185 | 0.8612 | |
|
| 0.3988 | 3.9583 | 190 | 0.8612 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.19.1 |
|
|
