|
--- |
|
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 |
|
|
