model
This model is a fine-tuned version of google/gemma-2-9b-it on the cdc0b2d9-493b-4cb1-87e8-8fb1e3f4b247 dataset. It achieves the following results on the evaluation set:
- Loss: 3.9434
- Rewards/chosen: -46.0543
- Rewards/rejected: -47.7041
- Rewards/accuracies: 0.6473
- Rewards/margins: 1.6497
- Logps/rejected: -4.7704
- Logps/chosen: -4.6054
- Logits/rejected: 14.6796
- Logits/chosen: 14.4459
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: 8e-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3.9873 | 1.0 | 7344 | 3.9434 | -46.0543 | -47.7041 | 0.6473 | 1.6497 | -4.7704 | -4.6054 | 14.6796 | 14.4459 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.0
- Datasets 2.21.0
- Tokenizers 0.20.2
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