Model: jackf857/llama-3-8b-base-new-dpo-harmless-s_star0.6-q_t0.4 Source: Original Platform
library_name, base_model, tags, datasets, model-index
| library_name | base_model | tags | datasets | model-index | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | W-61/llama-3-8b-base-sft-hh-harmless-4xh200 |
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llama3-8b-base-new-method-s_star0.6
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: 0.5591
- Fcm Dpo/beta: 0.0089
- Margin Dpo/margin Mean: 55.2826
- Margin Dpo/margin Std: 95.3567
- Logps/chosen: -205.2188
- Logps/rejected: -265.1909
- Logps/ref Chosen: -74.8595
- Logps/ref Rejected: -79.5490
- Logits/chosen: 0.7206
- Logits/rejected: 0.6751
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 | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.0505 | 0.3023 | 200 | 0.5490 | 0.0445 | 12.8367 | 21.5327 | -94.9354 | -112.4616 | -74.8595 | -79.5490 | 0.4353 | 0.3850 |
| 1.0738 | 0.6047 | 400 | 0.5614 | 0.0103 | 44.9123 | 77.2791 | -176.5743 | -226.1761 | -74.8595 | -79.5490 | 0.6246 | 0.5775 |
| 1.1653 | 0.9070 | 600 | 0.5591 | 0.0089 | 55.2826 | 95.3567 | -205.2188 | -265.1909 | -74.8595 | -79.5490 | 0.7206 | 0.6751 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4
Description