metadata
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C017_random_sample_llama3-8b-base_pretrain_20240504_182259
results: []
C017_random_sample_llama3-8b-base_pretrain_20240504_182259
This model is a fine-tuned version of /data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base on the C017_random_sample_data dataset. It achieves the following results on the evaluation set:
- Loss: 2.4690
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 |
|---|---|---|---|
| 2.5442 | 0.2028 | 200 | 2.5552 |
| 2.5376 | 0.4057 | 400 | 2.5096 |
| 2.4487 | 0.6085 | 600 | 2.4831 |
| 2.5324 | 0.8114 | 800 | 2.4690 |
| 2.265 | 1.0142 | 1000 | 2.4733 |
| 2.3002 | 1.2170 | 1200 | 2.4736 |
| 2.29 | 1.4199 | 1400 | 2.4734 |
| 2.2566 | 1.6227 | 1600 | 2.4725 |
| 2.3052 | 1.8256 | 1800 | 2.4721 |
| 2.2702 | 2.0284 | 2000 | 2.4734 |
| 2.2411 | 2.2312 | 2200 | 2.4746 |
| 2.2413 | 2.4341 | 2400 | 2.4749 |
| 2.216 | 2.6369 | 2600 | 2.4749 |
| 2.2696 | 2.8398 | 2800 | 2.4747 |
| 2.2455 | 3.0426 | 3000 | 2.4752 |
| 2.216 | 3.2454 | 3200 | 2.4753 |
| 2.2348 | 3.4483 | 3400 | 2.4757 |
| 2.238 | 3.6511 | 3600 | 2.4753 |
| 2.2349 | 3.8540 | 3800 | 2.4752 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1