---
license: apache-2.0
base_model: DatPySci/pythia-1b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- DatPySci/iter0
model-index:
- name: pythia-1b-kto-iter0
  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. -->

# pythia-1b-kto-iter0

This model is a fine-tuned version of [DatPySci/pythia-1b-sft-full](https://huggingface.co/DatPySci/pythia-1b-sft-full) on the DatPySci/iter0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2591
- Rewards/real: 0.0604
- Rewards/generated: -1.0267
- Rewards/accuracies: 0.9460
- Rewards/margins: 1.0871
- Logps/generated: -570.8114
- Logps/real: -468.1696
- Logits/generated: 0.2253
- Logits/real: -0.2820

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:|
| 0.2932        | 0.38  | 300  | 0.2962          | 0.0718       | -0.7855           | 0.9220             | 0.8572          | -568.3989       | -468.0556  | 0.2554           | -0.2530     |
| 0.2689        | 0.77  | 600  | 0.2591          | 0.0604       | -1.0267           | 0.9460             | 1.0871          | -570.8114       | -468.1696  | 0.2253           | -0.2820     |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2