
<!-- 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. -->

# pythia-1b-spin-iter2

This model is a fine-tuned version of [DatPySci/pythia-1b-spin-iter1](https://huggingface.co/DatPySci/pythia-1b-spin-iter1) on the DatPySci/SPIN_iter2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3756
- Rewards/real: -0.0566
- Rewards/generated: -1.0410
- Rewards/accuracies: 0.9325
- Rewards/margins: 0.9844
- Logps/generated: -625.5765
- Logps/real: -452.6451
- Logits/generated: -0.0007
- Logits/real: -0.3650

## 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 | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:|
| 0.6169        | 0.24  | 100  | 0.6080          | 0.0108       | -0.2094           | 0.7025             | 0.2202          | -617.2608       | -451.9713  | 0.0774           | -0.2910     |
| 0.5059        | 0.47  | 200  | 0.4924          | -0.0049      | -0.5301           | 0.8342             | 0.5252          | -620.4679       | -452.1286  | 0.0417           | -0.3257     |
| 0.4253        | 0.71  | 300  | 0.4385          | -0.0302      | -0.7428           | 0.8942             | 0.7126          | -622.5947       | -452.3810  | 0.0240           | -0.3426     |
| 0.4138        | 0.94  | 400  | 0.4062          | -0.0435      | -0.8766           | 0.9125             | 0.8331          | -623.9332       | -452.5141  | 0.0104           | -0.3555     |
| 0.378         | 1.18  | 500  | 0.3925          | -0.0468      | -0.9628           | 0.9025             | 0.9160          | -624.7952       | -452.5474  | 0.0025           | -0.3620     |
| 0.3781        | 1.41  | 600  | 0.3830          | -0.0564      | -1.0048           | 0.9100             | 0.9484          | -625.2144       | -452.6428  | 0.0003           | -0.3643     |
| 0.3824        | 1.65  | 700  | 0.3784          | -0.0483      | -1.0116           | 0.9100             | 0.9633          | -625.2828       | -452.5618  | 0.0023           | -0.3628     |
| 0.3911        | 1.88  | 800  | 0.3756          | -0.0566      | -1.0410           | 0.9325             | 0.9844          | -625.5765       | -452.6451  | -0.0007          | -0.3650     |


### Framework versions

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

{"license": "apache-2.0", "tags": ["alignment-handbook", "generated_from_trainer"], "datasets": ["DatPySci/SPIN_iter2"], "base_model": "DatPySci/pythia-1b-spin-iter1", "model-index": [{"name": "pythia-1b-spin-iter2", "results": []}]}
transformers safetensors gpt_neox text-generation alignment-handbook generated_from_trainer conversational dataset:DatPySci/SPIN_iter2 base_model:DatPySci/pythia-1b-spin-iter1 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us