metadata
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: lambda-llama-3-8b-ipo-test
results: []
lambda-llama-3-8b-ipo-test
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8938
- Rewards/chosen: -0.3750
- Rewards/rejected: -0.6076
- Rewards/accuracies: 0.7892
- Rewards/margins: 0.2326
- Logps/rejected: -3.1855
- Logps/chosen: -2.5684
- Logits/rejected: -3.0293
- Logits/chosen: -2.9592
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: 5e-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.1749 | 0.1744 | 100 | 1.0763 | -0.1732 | -0.3120 | 0.7892 | 0.1388 | -2.4465 | -2.0638 | -2.5676 | -2.5133 |
| 0.9802 | 0.3489 | 200 | 0.9501 | -0.3184 | -0.5302 | 0.8012 | 0.2118 | -2.9922 | -2.4269 | -2.7873 | -2.7230 |
| 0.9548 | 0.5233 | 300 | 0.9136 | -0.3761 | -0.6028 | 0.8163 | 0.2267 | -3.1736 | -2.5710 | -2.8788 | -2.8087 |
| 0.9834 | 0.6978 | 400 | 0.9041 | -0.3384 | -0.5537 | 0.8042 | 0.2153 | -3.0509 | -2.4770 | -2.9371 | -2.8667 |
| 0.9967 | 0.8722 | 500 | 0.8938 | -0.3750 | -0.6076 | 0.7892 | 0.2326 | -3.1855 | -2.5684 | -3.0293 | -2.9592 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1