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---
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
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