transformers tensorboard safetensors mistral text-generation alignment-handbook generated_from_trainer conversational dataset:HuggingFaceH4/ultrafeedback_binarized base_model:Intel/neural-chat-7b-v3-1 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: Intel/neural-chat-7b-v3-1
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: juanako-7b-v2-UNA-v3
  results: []
---

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# juanako-7b-v2-UNA-v3

This model is a fine-tuned version of [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4658
- Rewards/chosen: -0.6178
- Rewards/rejected: -1.7640
- Rewards/accuracies: 0.7622
- Rewards/margins: 1.1462
- Logps/rejected: -239.1435
- Logps/chosen: -227.6597
- Logits/rejected: -2.2452
- Logits/chosen: -2.4812

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 14
- gradient_accumulation_steps: 16
- total_train_batch_size: 224
- total_eval_batch_size: 14
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4855        | 0.25  | 69   | 0.4897          | -0.7296        | -1.8563          | 0.7413             | 1.1266          | -240.0657      | -228.7776    | -2.2474         | -2.4843       |
| 0.4835        | 0.5   | 138  | 0.4734          | -0.5055        | -1.5652          | 0.7483             | 1.0597          | -237.1553      | -226.5366    | -2.2448         | -2.4811       |
| 0.5193        | 0.75  | 207  | 0.4717          | -0.6888        | -1.7561          | 0.7343             | 1.0673          | -239.0642      | -228.3696    | -2.2426         | -2.4783       |
| 0.4514        | 1.0   | 276  | 0.4658          | -0.6178        | -1.7640          | 0.7622             | 1.1462          | -239.1435      | -227.6597    | -2.2452         | -2.4812       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
