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---
license: apache-2.0
base_model: ondevicellm/tinyllama_moe
tags:
- alignment-handbook
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
- ondevicellm/SlimOrca
model-index:
- name: tinyllama_moe_sft_ultrachat-slimorca
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_ultrachat-slimorca
This model is a fine-tuned version of [ondevicellm/tinyllama_moe](https://huggingface.co/ondevicellm/tinyllama_moe) on the HuggingFaceH4/ultrachat_200k and the ondevicellm/SlimOrca datasets.
It achieves the following results on the evaluation set:
- Loss: 1.1526
## 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_steps: 120
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4601 | 0.05 | 100 | 1.3361 |
| 1.3324 | 0.1 | 200 | 1.2566 |
| 1.2946 | 0.14 | 300 | 1.2279 |
| 1.2767 | 0.19 | 400 | 1.2111 |
| 1.2298 | 0.24 | 500 | 1.1995 |
| 1.2247 | 0.29 | 600 | 1.1902 |
| 1.2208 | 0.34 | 700 | 1.1833 |
| 1.2375 | 0.39 | 800 | 1.1775 |
| 1.2038 | 0.43 | 900 | 1.1726 |
| 1.1926 | 0.48 | 1000 | 1.1683 |
| 1.1933 | 0.53 | 1100 | 1.1649 |
| 1.1893 | 0.58 | 1200 | 1.1618 |
| 1.2029 | 0.63 | 1300 | 1.1593 |
| 1.2201 | 0.68 | 1400 | 1.1572 |
| 1.1741 | 0.72 | 1500 | 1.1557 |
| 1.1813 | 0.77 | 1600 | 1.1545 |
| 1.1668 | 0.82 | 1700 | 1.1536 |
| 1.1495 | 0.87 | 1800 | 1.1530 |
| 1.1595 | 0.92 | 1900 | 1.1527 |
| 1.1607 | 0.97 | 2000 | 1.1526 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0
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