transformers tensorboard safetensors mixtral text-generation alignment-handbook generated_from_trainer trl sft conversational dataset:HuggingFaceH4/ultrachat_200k base_model:ondevicellm/tinyllama_moe license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: ondevicellm/tinyllama_moe
tags:
- alignment-handbook
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: tinyllama_moe_sft_ultrachat200k_v2
  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. -->

# tinyllama_moe_sft_ultrachat200k_v2

This model is a fine-tuned version of [ondevicellm/tinyllama_moe](https://huggingface.co/ondevicellm/tinyllama_moe) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1593

## 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.336         | 0.09  | 100  | 1.3140          |
| 1.2426        | 0.18  | 200  | 1.2376          |
| 1.2083        | 0.26  | 300  | 1.2100          |
| 1.1862        | 0.35  | 400  | 1.1934          |
| 1.1567        | 0.44  | 500  | 1.1820          |
| 1.1777        | 0.53  | 600  | 1.1737          |
| 1.1666        | 0.61  | 700  | 1.1677          |
| 1.1531        | 0.7   | 800  | 1.1636          |
| 1.1525        | 0.79  | 900  | 1.1610          |
| 1.1396        | 0.88  | 1000 | 1.1596          |
| 1.1681        | 0.96  | 1100 | 1.1593          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.0
