metadata
library_name: transformers
base_model: Jennny/llama3_8b_sft_ultrafb
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_8b_general_rm_full
results: []
llama3_8b_general_rm_full
This model is a fine-tuned version of Jennny/llama3_8b_sft_ultrafb on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2676
- Accuracy: 0.8858
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- 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 |
|---|---|---|---|---|
| 0.3173 | 0.1549 | 50 | 0.3212 | 0.8622 |
| 0.3037 | 0.3098 | 100 | 0.2959 | 0.8742 |
| 0.2982 | 0.4647 | 150 | 0.3012 | 0.8735 |
| 0.2857 | 0.6196 | 200 | 0.2818 | 0.8823 |
| 0.2773 | 0.7744 | 250 | 0.2716 | 0.8853 |
| 0.2691 | 0.9293 | 300 | 0.2676 | 0.8858 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3