e8efbe1ca9
Model: W-61/llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.4-20260429-230725 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-ultrachat-8xh200 |
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llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.4-20260429-230725
This model is a fine-tuned version of W-61/llama-3-8b-base-sft-ultrachat-8xh200 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6016
- Fcm Dpo/beta: 0.0024
- Margin Dpo/margin Mean: 110.8150
- Margin Dpo/margin Std: 193.4060
- Logps/chosen: -564.3179
- Logps/rejected: -654.2360
- Logps/ref Chosen: -287.8268
- Logps/ref Rejected: -266.9300
- Kl/chosen Kl Mean: -276.4911
- Kl/rejected Kl Mean: -387.3060
- Kl/mean: -331.8985
- Kl/std: 172.4884
- Logits/chosen: -0.8581
- Logits/rejected: -0.8405
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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 | Kl/chosen Kl Mean | Kl/rejected Kl Mean | Kl/mean | Kl/std | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4.8804 | 0.4188 | 200 | 0.5899 | 0.0054 | 57.3948 | 97.5992 | -411.1033 | -447.6013 | -287.8268 | -266.9300 | -123.2765 | -180.6713 | -151.9739 | 89.3493 | -0.9016 | -0.8836 |
| 4.8661 | 0.8377 | 400 | 0.6016 | 0.0024 | 110.8150 | 193.4060 | -564.3179 | -654.2360 | -287.8268 | -266.9300 | -276.4911 | -387.3060 | -331.8985 | 172.4884 | -0.8581 | -0.8405 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4