ab10c6b4c0
Model: jackf857/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun Source: Original Platform
3.3 KiB
3.3 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-hh-helpful-4xh200 |
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llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
This model is a fine-tuned version of W-61/llama-3-8b-base-sft-hh-helpful-4xh200 on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set:
- Loss: 0.6074
- Fcm Dpo/beta: 0.0011
- Fcm Dpo/q T: 0.4332
- Fcm Dpo/delta: 0.0239
- Fcm Dpo/margin: 270.7279
- Margin Dpo/margin Mean: 270.7279
- Margin Dpo/margin Std: 601.7490
- Logps/chosen: -823.2324
- Logps/rejected: -1101.7070
- Logps/ref Chosen: -79.0510
- Logps/ref Rejected: -86.7979
- Logits/chosen: -1.0197
- Logits/rejected: -1.0177
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: 2
- total_train_batch_size: 64
- 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 | Fcm Dpo/beta | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.0801 | 0.2937 | 200 | 0.6239 | 0.0049 | 0.4392 | 0.0321 | 58.0086 | 58.0086 | 147.6546 | -225.8390 | -291.5945 | -79.0510 | -86.7979 | -0.3472 | -0.3330 |
| 1.0433 | 0.5874 | 400 | 0.6033 | 0.0019 | 0.4336 | 0.0376 | 156.9007 | 156.9006 | 328.4540 | -532.2333 | -696.8809 | -79.0510 | -86.7979 | -0.5230 | -0.5119 |
| 1.1393 | 0.8811 | 600 | 0.6074 | 0.0011 | 0.4332 | 0.0239 | 270.7279 | 270.7279 | 601.7490 | -823.2324 | -1101.7070 | -79.0510 | -86.7979 | -1.0197 | -1.0177 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4