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# pythia-1b-spin-iter1

This model is a fine-tuned version of [DatPySci/pythia-1b-sft-50k](https://huggingface.co/DatPySci/pythia-1b-sft-50k) on the DatPySci/SPIN_iter1 dataset.
It achieves the following results on the evaluation set:
- Logits/generated: 0.1219
- Logits/real: -0.2658
- Logps/generated: -642.4531
- Logps/real: -451.7076
- Loss: 0.4631
- Rewards/accuracies: 0.8933
- Rewards/generated: -0.5136
- Rewards/margins: 0.6246
- Rewards/real: 0.1110

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Logits/generated | Logits/real | Logps/generated | Logps/real | Validation Loss | Rewards/accuracies | Rewards/generated | Rewards/margins | Rewards/real |
|:-------------:|:-----:|:----:|:----------------:|:-----------:|:---------------:|:----------:|:---------------:|:------------------:|:-----------------:|:---------------:|:------------:|
| 0.5506        | 0.47  | 100  | 0.1437           | -0.2435     | -640.1943       | -452.0957  | 0.5553          | 0.7983             | -0.2878           | 0.3599          | 0.0722       |
| 0.4951        | 0.94  | 200  | 0.1263           | -0.2623     | -641.7112       | -451.9472  | 0.4917          | 0.8800             | -0.4395           | 0.5265          | 0.0870       |
| 0.4575        | 1.41  | 300  | 0.1216           | -0.2660     | -642.3175       | -451.8161  | 0.4704          | 0.8758             | -0.5001           | 0.6002          | 0.1001       |
| 0.4564        | 1.88  | 400  | 0.1219           | -0.2658     | -642.4531       | -451.7076  | 0.4631          | 0.8933             | -0.5136           | 0.6246          | 0.1110       |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_DatPySci__pythia-1b-spin-iter1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |32.85|
|AI2 Reasoning Challenge (25-Shot)|30.55|
|HellaSwag (10-Shot)              |49.26|
|MMLU (5-Shot)                    |24.46|
|TruthfulQA (0-shot)              |36.89|
|Winogrande (5-shot)              |53.59|
|GSM8k (5-shot)                   | 2.35|


{"license": "apache-2.0", "tags": ["alignment-handbook", "generated_from_trainer"], "datasets": ["DatPySci/SPIN_iter1"], "base_model": "DatPySci/pythia-1b-sft-50k", "model-index": [{"name": "pythia-1b-spin-iter1", "results": []}]}
transformers safetensors gpt_neox text-generation alignment-handbook generated_from_trainer conversational dataset:DatPySci/SPIN_iter1 base_model:DatPySci/pythia-1b-sft-50k license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us