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---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C014_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. -->
# C014_llama3-8b-base_instruct_20240428_005832
This model is a fine-tuned version of [./output/training_results/C014_llama3-8b-base_pretrain_20240428_005832/](https://huggingface.co/./output/training_results/C014_llama3-8b-base_pretrain_20240428_005832/) on the instructions_curated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8149
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9832 | 0.0208 | 1 | 0.9730 |
| 0.9463 | 0.1042 | 5 | 0.9421 |
| 0.8488 | 0.2083 | 10 | 0.8247 |
| 0.7833 | 0.3125 | 15 | 0.8149 |
| 0.7797 | 0.4167 | 20 | 0.8403 |
| 0.8542 | 0.5208 | 25 | 0.8670 |
| 0.8895 | 0.625 | 30 | 0.8718 |
| 0.8519 | 0.7292 | 35 | 0.8592 |
| 0.8224 | 0.8333 | 40 | 0.8491 |
| 0.8538 | 0.9375 | 45 | 0.8384 |
| 0.6569 | 1.0417 | 50 | 0.8295 |
| 0.437 | 1.1458 | 55 | 0.8457 |
| 0.4405 | 1.25 | 60 | 0.8668 |
| 0.4331 | 1.3542 | 65 | 0.8671 |
| 0.448 | 1.4583 | 70 | 0.8597 |
| 0.4673 | 1.5625 | 75 | 0.8514 |
| 0.4298 | 1.6667 | 80 | 0.8474 |
| 0.4252 | 1.7708 | 85 | 0.8458 |
| 0.4429 | 1.875 | 90 | 0.8451 |
| 0.4484 | 1.9792 | 95 | 0.8450 |
| 0.3634 | 2.0833 | 100 | 0.8455 |
| 0.3876 | 2.1875 | 105 | 0.8467 |
| 0.3717 | 2.2917 | 110 | 0.8481 |
| 0.387 | 2.3958 | 115 | 0.8494 |
| 0.3561 | 2.5 | 120 | 0.8505 |
| 0.4219 | 2.6042 | 125 | 0.8516 |
| 0.3798 | 2.7083 | 130 | 0.8527 |
| 0.3551 | 2.8125 | 135 | 0.8537 |
| 0.3827 | 2.9167 | 140 | 0.8546 |
| 0.3938 | 3.0208 | 145 | 0.8556 |
| 0.3805 | 3.125 | 150 | 0.8565 |
| 0.3813 | 3.2292 | 155 | 0.8574 |
| 0.3894 | 3.3333 | 160 | 0.8582 |
| 0.3603 | 3.4375 | 165 | 0.8589 |
| 0.3515 | 3.5417 | 170 | 0.8597 |
| 0.3433 | 3.6458 | 175 | 0.8605 |
| 0.3511 | 3.75 | 180 | 0.8614 |
| 0.3599 | 3.8542 | 185 | 0.8620 |
| 0.3994 | 3.9583 | 190 | 0.8621 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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