8162a32e06
Model: W-61/llama-3-8b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260417-233539 Source: Original Platform
86 lines
4.8 KiB
Markdown
86 lines
4.8 KiB
Markdown
---
|
|
library_name: transformers
|
|
base_model: llama-3-8b-base-sft-hh-harmless-4xh200-batch-64
|
|
tags:
|
|
- alignment-handbook
|
|
- beta-dpo
|
|
- generated_from_trainer
|
|
datasets:
|
|
- Anthropic/hh-rlhf
|
|
model-index:
|
|
- name: llama-3-8b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260417-233539
|
|
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. -->
|
|
|
|
# llama-3-8b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260417-233539
|
|
|
|
This model is a fine-tuned version of [llama-3-8b-base-sft-hh-harmless-4xh200-batch-64](https://huggingface.co/llama-3-8b-base-sft-hh-harmless-4xh200-batch-64) on the Anthropic/hh-rlhf dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.8203
|
|
- Beta Dpo/beta: 0.1705
|
|
- Beta Dpo/loss Margin Mean: 16.6192
|
|
- Beta Dpo/beta Margin Mean: 3.5151
|
|
- Beta Dpo/beta Margin Std: 4.7567
|
|
- Beta Dpo/beta Margin Grad Mean: -0.3392
|
|
- Beta Dpo/beta Margin Grad Std: 0.2229
|
|
- Beta Dpo/gap Mean: 16.4768
|
|
- Beta Dpo/gap Std: 28.4131
|
|
- Beta Dpo/beta Used Raw: 0.1085
|
|
- Beta Dpo/beta Used: 0.1705
|
|
- Beta Dpo/mask Keep Frac: 1.0
|
|
- Logits/chosen: 0.5021
|
|
- Logits/rejected: 0.4487
|
|
|
|
## 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: 8
|
|
- eval_batch_size: 8
|
|
- seed: 42
|
|
- distributed_type: multi-GPU
|
|
- num_devices: 4
|
|
- gradient_accumulation_steps: 2
|
|
- total_train_batch_size: 64
|
|
- total_eval_batch_size: 32
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
|
- lr_scheduler_type: cosine
|
|
- lr_scheduler_warmup_ratio: 0.1
|
|
- num_epochs: 1
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Beta Dpo/beta | Beta Dpo/loss Margin Mean | Beta Dpo/beta Margin Mean | Beta Dpo/beta Margin Std | Beta Dpo/beta Margin Grad Mean | Beta Dpo/beta Margin Grad Std | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected |
|
|
|:-------------:|:------:|:----:|:---------------:|:-------------:|:-------------------------:|:-------------------------:|:------------------------:|:------------------------------:|:-----------------------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
|
|
| 1.3014 | 0.1512 | 100 | 0.6391 | 0.1183 | 1.3224 | 0.1789 | 0.4749 | -0.4595 | 0.1057 | 1.0180 | 3.3360 | 0.1183 | 0.1183 | 1.0 | 0.2572 | 0.2207 |
|
|
| 0.9318 | 0.3023 | 200 | 0.5939 | 0.0752 | 9.0802 | 0.8670 | 1.1566 | -0.3975 | 0.1333 | 10.1709 | 15.2637 | 0.0346 | 0.0752 | 1.0 | 0.4250 | 0.3786 |
|
|
| 1.1289 | 0.4535 | 300 | 0.6938 | 0.1151 | 14.7143 | 2.1435 | 2.8181 | -0.3684 | 0.1767 | 15.7264 | 23.2621 | 0.0393 | 0.1151 | 1.0 | 0.5036 | 0.4522 |
|
|
| 1.3777 | 0.6047 | 400 | 0.6486 | 0.0698 | 13.2713 | 1.2326 | 1.6702 | -0.4066 | 0.1228 | 15.5137 | 23.8374 | -0.0345 | 0.0698 | 1.0 | 0.4392 | 0.3876 |
|
|
| 1.1911 | 0.7559 | 500 | 0.6888 | 0.0936 | 16.0572 | 1.9620 | 2.5727 | -0.3866 | 0.1471 | 17.9087 | 28.7161 | -0.0111 | 0.0936 | 1.0 | 0.5027 | 0.4490 |
|
|
| 1.0347 | 0.9070 | 600 | 0.8203 | 0.1705 | 16.6192 | 3.5151 | 4.7567 | -0.3392 | 0.2229 | 16.4768 | 28.4131 | 0.1085 | 0.1705 | 1.0 | 0.5021 | 0.4487 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.51.0
|
|
- Pytorch 2.3.1+cu121
|
|
- Datasets 2.21.0
|
|
- Tokenizers 0.21.4
|