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# ifable/gemma-2-Ifable-9B


It achieves the following results on the evaluation set:
- Loss: 1.0163
- Rewards/chosen: -21.6822
- Rewards/rejected: -47.8754
- Rewards/accuracies: 0.9167
- Rewards/margins: 26.1931
- Logps/rejected: -4.7875
- Logps/chosen: -2.1682
- Logits/rejected: -17.0475
- Logits/chosen: -12.0041
- Sft Loss: 0.0184

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 | Sft Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.4444        | 0.9807 | 35   | 1.0163          | -21.6822       | -47.8754         | 0.9167             | 26.1931         | -4.7875        | -2.1682      | -17.0475        | -12.0041      | 0.0184   |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.20.0
- Tokenizers 0.19.1