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---
license: apache-2.0
base_model: AmberYifan/mistral-safe-sft-full
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- AmberYifan/sft-spin-kcenter-5k
model-index:
- name: sft-spin-kcenter-5k
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sft-spin-kcenter-5k
This model is a fine-tuned version of [AmberYifan/mistral-safe-sft-full](https://huggingface.co/AmberYifan/mistral-safe-sft-full) on the AmberYifan/sft-spin-kcenter-5k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0181
- Rewards/real: 1.4812
- Rewards/generated: 1.4157
- Rewards/accuracies: 0.0812
- Rewards/margins: 0.0655
- Logps/generated: -57.7408
- Logps/real: -16.8189
- Logits/generated: -2.6921
- Logits/real: -2.4190
## 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
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real |
|:-------------:|:------:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:|
| 0.3429 | 0.6369 | 100 | 1.0181 | 1.4812 | 1.4157 | 0.0812 | 0.0655 | -57.7408 | -16.8189 | -2.6921 | -2.4190 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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