4c5ec42aaa
Model: W-61/llama-3-8b-base-new-dpo-hh-harmless-s_star1.0-4xh200-batch-64-20260421-213851 Source: Original Platform
3.2 KiB
3.2 KiB
library_name, base_model, tags, datasets, model-index
| library_name | base_model | tags | datasets | model-index | |||||||||
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| transformers | W-61/llama-3-8b-base-sft-hh-harmless-4xh200 |
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llama-3-8b-base-new-dpo-hh-harmless-s_star1.0-4xh200-batch-64-20260421-213851
This model is a fine-tuned version of W-61/llama-3-8b-base-sft-hh-harmless-4xh200 on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set:
- Loss: 0.5467
- Fcm Dpo/beta: 0.2268
- Fcm Dpo/q T: 0.3412
- Fcm Dpo/delta: -0.0017
- Fcm Dpo/margin: 4.4089
- Margin Dpo/margin Mean: 4.4089
- Margin Dpo/margin Std: 7.2504
- Logps/chosen: -82.5570
- Logps/rejected: -91.6554
- Logps/ref Chosen: -74.8595
- Logps/ref Rejected: -79.5490
- Logits/chosen: 0.2724
- Logits/rejected: 0.2290
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 | Fcm Dpo/beta | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.9878 | 0.3023 | 200 | 0.5709 | 0.4418 | 0.3475 | 0.0198 | 2.2173 | 2.2173 | 3.8804 | -79.5152 | -86.4220 | -74.8595 | -79.5490 | 0.2313 | 0.1912 |
| 0.966 | 0.6047 | 400 | 0.5573 | 0.2747 | 0.3451 | 0.0194 | 3.5687 | 3.5687 | 6.0461 | -81.6850 | -89.9432 | -74.8595 | -79.5490 | 0.2557 | 0.2135 |
| 1.122 | 0.9070 | 600 | 0.5467 | 0.2268 | 0.3412 | -0.0017 | 4.4089 | 4.4089 | 7.2504 | -82.5570 | -91.6554 | -74.8595 | -79.5490 | 0.2724 | 0.2290 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4