transformers tensorboard safetensors gpt2 text-generation generated_from_trainer conversational base_model:SebastianSchramm/Cerebras-GPT-111M-instruction-sft-lora-merged autotrain_compatible endpoints_compatible text-generation-inference region:us
---
base_model: SebastianSchramm/Cerebras-GPT-111M-instruction-sft-lora-merged
tags:
- generated_from_trainer
model-index:
- name: Cerebras-GPT-111M-instruction-sft-lora-merged-dpo-lora
  results: []
---

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# Cerebras-GPT-111M-instruction-sft-lora-merged-dpo-lora

This model is a fine-tuned version of [SebastianSchramm/Cerebras-GPT-111M-instruction-sft-lora-merged](https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction-sft-lora-merged) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6203
- Rewards/chosen: 0.8184
- Rewards/rejected: 0.4678
- Rewards/accuracies: 0.6555
- Rewards/margins: 0.3506
- Logps/rejected: -797.4490
- Logps/chosen: -1064.1462
- Logits/rejected: -2.6967
- Logits/chosen: -2.9346

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6555        | 0.34  | 300  | 0.6536          | 0.5523         | 0.3662           | 0.6271             | 0.1862          | -798.4653      | -1066.8068   | -2.7199         | -2.9594       |
| 0.615         | 0.68  | 600  | 0.6352          | 0.7267         | 0.4534           | 0.6380             | 0.2732          | -797.5925      | -1065.0635   | -2.7194         | -2.9580       |
| 0.6313        | 1.02  | 900  | 0.6278          | 0.7792         | 0.4662           | 0.6440             | 0.3131          | -797.4653      | -1064.5378   | -2.7117         | -2.9469       |
| 0.6218        | 1.36  | 1200 | 0.6295          | 0.7738         | 0.4669           | 0.6457             | 0.3069          | -797.4579      | -1064.5920   | -2.7035         | -2.9401       |
| 0.6311        | 1.71  | 1500 | 0.6212          | 0.7817         | 0.4456           | 0.6654             | 0.3361          | -797.6708      | -1064.5128   | -2.7073         | -2.9437       |
| 0.6107        | 2.05  | 1800 | 0.6223          | 0.8065         | 0.4674           | 0.6572             | 0.3391          | -797.4526      | -1064.2653   | -2.7009         | -2.9373       |
| 0.6146        | 2.39  | 2100 | 0.6190          | 0.8141         | 0.4648           | 0.6698             | 0.3494          | -797.4793      | -1064.1887   | -2.6988         | -2.9353       |
| 0.6347        | 2.73  | 2400 | 0.6214          | 0.8118         | 0.4631           | 0.6654             | 0.3487          | -797.4959      | -1064.2124   | -2.6962         | -2.9342       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
