443dbe5858
Model: jackf857/llama-3-8b-base-slic-hf-ultrafeedback-4xh200-batch-128-20260428-054623 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-slic-hf-ultrafeedback-4xh200-batch-128-20260428-054623
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: 341.8599
- Rewards/chosen: -260.7975
- Rewards/rejected: -247.1082
- Rewards/accuracies: 0.4935
- Rewards/margins: -13.6894
- Logps/chosen: -260.7975
- Logps/rejected: -247.1082
- Slic/rank Loss: 81.0624
- Slic/ce Loss: 260.7975
- Logits/chosen: -0.6037
- Logits/rejected: -0.6097
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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Slic/rank Loss | Slic/ce Loss | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2735.9918 | 0.4188 | 200 | 345.5438 | -262.1006 | -246.2827 | 0.4885 | -15.8179 | -262.1006 | -246.2827 | 83.4432 | 262.1006 | -0.6110 | -0.6187 |
| 2791.6219 | 0.8377 | 400 | 341.8599 | -260.7975 | -247.1082 | 0.4935 | -13.6894 | -260.7975 | -247.1082 | 81.0624 | 260.7975 | -0.6037 | -0.6097 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4