1e65d1513d
Model: W-61/llama3-8b-base-new-method-s_star0.6-20260425-180936 Source: Original Platform
2.7 KiB
2.7 KiB
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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llama3-8b-base-new-method-s_star0.6-20260425-180936
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: 0.5352
- Fcm Dpo/beta: 0.0110
- Margin Dpo/margin Mean: 54.2375
- Margin Dpo/margin Std: 83.0790
- Logps/chosen: -383.9891
- Logps/rejected: -417.3312
- Logps/ref Chosen: -287.8268
- Logps/ref Rejected: -266.9314
- Logits/chosen: -0.8407
- Logits/rejected: -0.8346
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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4.6087 | 0.4188 | 200 | 0.5497 | 0.0189 | 29.5673 | 48.3802 | -320.8928 | -329.5647 | -287.8268 | -266.9314 | -0.8679 | -0.8610 |
| 4.3167 | 0.8377 | 400 | 0.5352 | 0.0110 | 54.2375 | 83.0790 | -383.9891 | -417.3312 | -287.8268 | -266.9314 | -0.8407 | -0.8346 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4