53d019704e
Model: jackf857/llama-3-8b-base-r-dpo-ultrafeedback-4xH200-batch-128-rerun-2-runpod Source: Original Platform
2.9 KiB
2.9 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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llama-3-8b-base-r-dpo-ultrafeedback-4xh200-batch-128
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: 0.6649
- R Dpo/chosen Len: 286.9760
- R Dpo/rejected Len: 246.0880
- R Dpo/length Delta: 40.8880
- R Dpo/regularization Term: 4.0888
- Logps/chosen: -2847.3083
- Logps/rejected: -2499.7363
- Logps/ref Chosen: -288.6415
- Logps/ref Rejected: -265.9616
- Logits/chosen: -0.3397
- Logits/rejected: -0.3240
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 | R Dpo/chosen Len | R Dpo/rejected Len | R Dpo/length Delta | R Dpo/regularization Term | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6.4185 | 0.4188 | 200 | 0.7758 | 286.9760 | 246.0880 | 40.8880 | 4.0888 | -2812.3984 | -2464.0371 | -288.6415 | -265.9616 | -0.2286 | -0.2353 |
| 5.4191 | 0.8377 | 400 | 0.6649 | 286.9760 | 246.0880 | 40.8880 | 4.0888 | -2847.3083 | -2499.7363 | -288.6415 | -265.9616 | -0.3397 | -0.3240 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4