f172e34488
Model: jackf857/llama-3-8b-base-orpo-ultrafeedback-4xh200-rerun 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-orpo-ultrafeedback-4xh200-rerun
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: 1.2244
- Rewards/chosen: -0.0088
- Rewards/rejected: -0.0106
- Rewards/accuracies: 0.6028
- Rewards/margins: 0.0018
- Logps/rejected: -1.0607
- Logps/chosen: -0.8758
- Logits/rejected: -0.4873
- Logits/chosen: -0.5022
- Nll Loss: 1.2174
- Log Odds Ratio: -0.6565
- Log Odds Chosen: 0.2857
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: 4
- total_train_batch_size: 128
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 5.2395 | 0.4188 | 200 | 1.2644 | -0.0088 | -0.0107 | 0.6008 | 0.0018 | -1.0672 | -0.8826 | -0.4935 | -0.5068 | 1.2561 | -0.6568 | 0.2836 |
| 4.9046 | 0.8377 | 400 | 1.2244 | -0.0088 | -0.0106 | 0.6028 | 0.0018 | -1.0607 | -0.8758 | -0.4873 | -0.5022 | 1.2174 | -0.6565 | 0.2857 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4