7da87889a0
Model: W-61/llama-3-8b-base-new-dpo-hh-harmless-s_star0.85-4xh200-batch-64-20260421-213851 Source: Original Platform
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_star0.85-4xh200-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: 0.5165
- Fcm Dpo/beta: 0.0569
- Fcm Dpo/q T: 0.3487
- Fcm Dpo/delta: -0.0094
- Fcm Dpo/margin: 14.9295
- Margin Dpo/margin Mean: 14.9295
- Margin Dpo/margin Std: 22.6525
- Logps/chosen: -98.0102
- Logps/rejected: -117.6293
- Logps/ref Chosen: -74.8595
- Logps/ref Rejected: -79.5490
- Logits/chosen: 0.4599
- Logits/rejected: 0.4106
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.9883 | 0.3023 | 200 | 0.5559 | 0.2407 | 0.3572 | 0.0135 | 3.4733 | 3.4733 | 5.9732 | -82.1818 | -90.3446 | -74.8595 | -79.5490 | 0.2746 | 0.2309 |
| 0.999 | 0.6047 | 400 | 0.5336 | 0.0953 | 0.3534 | 0.0107 | 8.8040 | 8.8040 | 14.1650 | -88.0488 | -101.5423 | -74.8595 | -79.5490 | 0.3667 | 0.3186 |
| 1.1106 | 0.9070 | 600 | 0.5165 | 0.0569 | 0.3487 | -0.0094 | 14.9295 | 14.9295 | 22.6525 | -98.0102 | -117.6293 | -74.8595 | -79.5490 | 0.4599 | 0.4106 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4