metadata
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_rm
results: []
llama3_rm
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3581
- Accuracy: 0.8443
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: 2e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8063 | 0.0705 | 10 | 0.6141 | 0.7339 |
| 0.5355 | 0.1410 | 20 | 0.5117 | 0.7604 |
| 0.4811 | 0.2115 | 30 | 0.4766 | 0.7719 |
| 0.4922 | 0.2819 | 40 | 0.4512 | 0.7792 |
| 0.4919 | 0.3524 | 50 | 0.4428 | 0.8 |
| 0.476 | 0.4229 | 60 | 0.4174 | 0.8083 |
| 0.3965 | 0.4934 | 70 | 0.4047 | 0.8161 |
| 0.3523 | 0.5639 | 80 | 0.3918 | 0.8224 |
| 0.455 | 0.6344 | 90 | 0.3794 | 0.8344 |
| 0.4096 | 0.7048 | 100 | 0.3682 | 0.8396 |
| 0.3726 | 0.7753 | 110 | 0.3636 | 0.8417 |
| 0.3802 | 0.8458 | 120 | 0.3600 | 0.8448 |
| 0.3908 | 0.9163 | 130 | 0.3585 | 0.8427 |
| 0.4002 | 0.9868 | 140 | 0.3581 | 0.8443 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.1.2+cu121
- Datasets 4.4.1
- Tokenizers 0.19.1