|
--- |
|
license: apache-2.0 |
|
base_model: ondevicellm/tinyllama_moe_sft_ultrachat200k_v2_epochs3 |
|
tags: |
|
- alignment-handbook |
|
- generated_from_trainer |
|
- trl |
|
- dpo |
|
- generated_from_trainer |
|
datasets: |
|
- HuggingFaceH4/ultrafeedback_binarized |
|
model-index: |
|
- name: tinyllama_moe_dpo_ultrachat_v2_epochs3 |
|
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_dpo_ultrachat_v2_epochs3 |
|
|
|
This model is a fine-tuned version of [ondevicellm/tinyllama_moe_sft_ultrachat200k_v2_epochs3](https://huggingface.co/ondevicellm/tinyllama_moe_sft_ultrachat200k_v2_epochs3) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5855 |
|
- Rewards/chosen: -0.9040 |
|
- Rewards/rejected: -1.3959 |
|
- Rewards/accuracies: 0.7262 |
|
- Rewards/margins: 0.4918 |
|
- Logps/rejected: -442.2930 |
|
- Logps/chosen: -435.4489 |
|
- Logits/rejected: -2.3585 |
|
- Logits/chosen: -2.4345 |
|
|
|
## 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: 5e-07 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- 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: 96 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
|
| 0.6914 | 0.1 | 100 | 0.6913 | 0.0043 | -0.0005 | 0.6349 | 0.0048 | -302.7554 | -344.6115 | -2.9876 | -3.0405 | |
|
| 0.6836 | 0.21 | 200 | 0.6830 | 0.0149 | -0.0095 | 0.6448 | 0.0244 | -303.6508 | -343.5497 | -2.9700 | -3.0243 | |
|
| 0.6662 | 0.31 | 300 | 0.6712 | -0.0134 | -0.0687 | 0.6746 | 0.0553 | -309.5701 | -346.3836 | -2.9423 | -2.9976 | |
|
| 0.6538 | 0.42 | 400 | 0.6571 | -0.0814 | -0.1804 | 0.6766 | 0.0990 | -320.7438 | -353.1802 | -2.8979 | -2.9548 | |
|
| 0.6405 | 0.52 | 500 | 0.6448 | -0.1949 | -0.3451 | 0.6726 | 0.1502 | -337.2181 | -364.5344 | -2.8541 | -2.9120 | |
|
| 0.6394 | 0.63 | 600 | 0.6372 | -0.2303 | -0.4148 | 0.6825 | 0.1845 | -344.1863 | -368.0754 | -2.8147 | -2.8733 | |
|
| 0.6218 | 0.73 | 700 | 0.6313 | -0.2894 | -0.5107 | 0.6825 | 0.2213 | -353.7792 | -373.9845 | -2.7666 | -2.8269 | |
|
| 0.6035 | 0.84 | 800 | 0.6249 | -0.3614 | -0.6145 | 0.6845 | 0.2531 | -364.1536 | -381.1849 | -2.7056 | -2.7681 | |
|
| 0.6326 | 0.94 | 900 | 0.6204 | -0.5259 | -0.8008 | 0.6845 | 0.2749 | -382.7857 | -397.6345 | -2.6568 | -2.7207 | |
|
| 0.6103 | 1.05 | 1000 | 0.6145 | -0.5164 | -0.8178 | 0.6944 | 0.3014 | -384.4856 | -396.6823 | -2.6322 | -2.6969 | |
|
| 0.6002 | 1.15 | 1100 | 0.6116 | -0.5179 | -0.8325 | 0.6925 | 0.3146 | -385.9578 | -396.8333 | -2.6024 | -2.6688 | |
|
| 0.5729 | 1.26 | 1200 | 0.6083 | -0.5838 | -0.9200 | 0.7044 | 0.3362 | -394.7073 | -403.4271 | -2.5708 | -2.6376 | |
|
| 0.599 | 1.36 | 1300 | 0.6077 | -0.5206 | -0.8453 | 0.7103 | 0.3247 | -387.2310 | -397.1021 | -2.5454 | -2.6134 | |
|
| 0.5821 | 1.47 | 1400 | 0.6025 | -0.5941 | -0.9561 | 0.7063 | 0.3620 | -398.3106 | -404.4496 | -2.5211 | -2.5900 | |
|
| 0.574 | 1.57 | 1500 | 0.5977 | -0.6617 | -1.0471 | 0.7143 | 0.3854 | -407.4162 | -411.2178 | -2.4887 | -2.5593 | |
|
| 0.5716 | 1.67 | 1600 | 0.5955 | -0.6765 | -1.0870 | 0.7282 | 0.4105 | -411.4020 | -412.6956 | -2.4651 | -2.5369 | |
|
| 0.5477 | 1.78 | 1700 | 0.5904 | -0.8020 | -1.2430 | 0.7321 | 0.4410 | -427.0003 | -425.2423 | -2.4342 | -2.5079 | |
|
| 0.5718 | 1.88 | 1800 | 0.5898 | -0.7932 | -1.2439 | 0.7321 | 0.4507 | -427.0937 | -424.3631 | -2.4186 | -2.4928 | |
|
| 0.563 | 1.99 | 1900 | 0.5904 | -0.6874 | -1.1313 | 0.7202 | 0.4439 | -415.8328 | -413.7807 | -2.4223 | -2.4961 | |
|
| 0.5633 | 2.09 | 2000 | 0.5884 | -0.7564 | -1.2105 | 0.7262 | 0.4541 | -423.7504 | -420.6851 | -2.4073 | -2.4819 | |
|
| 0.5564 | 2.2 | 2100 | 0.5878 | -0.8150 | -1.2802 | 0.7262 | 0.4652 | -430.7243 | -426.5488 | -2.3948 | -2.4696 | |
|
| 0.5373 | 2.3 | 2200 | 0.5865 | -0.8791 | -1.3602 | 0.7341 | 0.4812 | -438.7289 | -432.9532 | -2.3795 | -2.4548 | |
|
| 0.5559 | 2.41 | 2300 | 0.5872 | -0.8476 | -1.3260 | 0.7242 | 0.4784 | -435.3001 | -429.7996 | -2.3743 | -2.4496 | |
|
| 0.5467 | 2.51 | 2400 | 0.5868 | -0.8483 | -1.3274 | 0.7222 | 0.4790 | -435.4401 | -429.8786 | -2.3697 | -2.4452 | |
|
| 0.5666 | 2.62 | 2500 | 0.5858 | -0.8754 | -1.3626 | 0.7242 | 0.4872 | -438.9631 | -432.5811 | -2.3641 | -2.4399 | |
|
| 0.5113 | 2.72 | 2600 | 0.5856 | -0.8942 | -1.3842 | 0.7242 | 0.4900 | -441.1211 | -434.4620 | -2.3604 | -2.4361 | |
|
| 0.5601 | 2.83 | 2700 | 0.5855 | -0.9040 | -1.3959 | 0.7262 | 0.4918 | -442.2930 | -435.4489 | -2.3585 | -2.4345 | |
|
| 0.5303 | 2.93 | 2800 | 0.5857 | -0.9003 | -1.3898 | 0.7242 | 0.4894 | -441.6805 | -435.0786 | -2.3581 | -2.4342 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.1.2+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.15.0 |
|
|
