---
license: apache-2.0
base_model: nnheui/pythia-1.4b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: pythia-1.4b-dpo-full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pythia-1.4b-dpo-full

This model is a fine-tuned version of [nnheui/pythia-1.4b-sft-full](https://huggingface.co/nnheui/pythia-1.4b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6257
- Rewards/chosen: -0.5234
- Rewards/rejected: -0.7812
- Rewards/accuracies: 0.6597
- Rewards/margins: 0.2578
- Logps/rejected: -416.0
- Logps/chosen: -446.0
- Logits/rejected: -1.2422
- Logits/chosen: -1.1953
- Logps/chosen Top Tokens: -0.0007
- Logps/rejected Top Tokens: -0.0007
- Logps/chosen Bottom Tokens: -14.375
- Logps/rejected Bottom Tokens: -14.3125

## 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: 5
- eval_batch_size: 5
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 4
- total_train_batch_size: 120
- total_eval_batch_size: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Logps/chosen Top Tokens | Logps/rejected Top Tokens | Logps/chosen Bottom Tokens | Logps/rejected Bottom Tokens |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:-----------------------:|:-------------------------:|:--------------------------:|:----------------------------:|
| 0.678         | 0.1963 | 100  | 0.6789          | -0.0275        | -0.0608          | 0.5881             | 0.0332          | -344.0         | -396.0       | -1.1562         | -1.0938       | -0.0009                 | -0.0009                   | -14.0625                   | -14.0                        |
| 0.645         | 0.3925 | 200  | 0.6489          | -0.2871        | -0.4238          | 0.6448             | 0.1367          | -380.0         | -422.0       | -1.2031         | -1.1562       | -0.0009                 | -0.0009                   | -14.375                    | -14.3125                     |
| 0.6396        | 0.5888 | 300  | 0.6304          | -0.4512        | -0.6797          | 0.6627             | 0.2275          | -406.0         | -438.0       | -1.2344         | -1.1875       | -0.0007                 | -0.0008                   | -14.375                    | -14.3125                     |
| 0.6102        | 0.7851 | 400  | 0.6268          | -0.5039        | -0.7617          | 0.6567             | 0.2578          | -414.0         | -444.0       | -1.2344         | -1.1875       | -0.0007                 | -0.0007                   | -14.3125                   | -14.25                       |
| 0.6084        | 0.9814 | 500  | 0.6259          | -0.5234        | -0.7852          | 0.6567             | 0.2617          | -416.0         | -446.0       | -1.2422         | -1.1953       | -0.0007                 | -0.0007                   | -14.375                    | -14.3125                     |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1