---
library_name: transformers
base_model: kykim0/Llama-2-7b-ultrachat200k-2e
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: Llama-2-7b-ultrachat-syn
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-2-7b-ultrachat-syn

This model is a fine-tuned version of [kykim0/Llama-2-7b-ultrachat200k-2e](https://huggingface.co./kykim0/Llama-2-7b-ultrachat200k-2e) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0863

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0994        | 0.9984 | 156  | 0.0907          |
| 0.0916        | 1.9968 | 312  | 0.0863          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.19.1