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# stealth-finance-v3-adapter

This model is a fine-tuned version of [jan-hq/stealth-v1.3](https://huggingface.co/jan-hq/stealth-v1.3) on the jan-hq/distilabel_dpo_pairs_binarized and the jan-hq/finance_dataset_subset_binarized datasets.
It achieves the following results on the evaluation set:
- Loss: 1.4276

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2692        | 0.99  | 55   | 1.4805          |
| 1.2135        | 1.99  | 111  | 1.4335          |
| 1.2208        | 2.96  | 165  | 1.4276          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
{"license": "apache-2.0", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "sft", "generated_from_trainer"], "datasets": ["jan-hq/distilabel_dpo_pairs_binarized", "jan-hq/finance_dataset_subset_binarized"], "base_model": "jan-hq/stealth-v1.3", "model-index": [{"name": "stealth-finance-v3-adapter", "results": []}]}
peft safetensors mistral alignment-handbook generated_from_trainer trl sft dataset:jan-hq/distilabel_dpo_pairs_binarized dataset:jan-hq/finance_dataset_subset_binarized base_model:jan-hq/stealth-v1.3 license:apache-2.0 region:us