|
--- |
|
license: cc-by-nc-4.0 |
|
tags: |
|
- trl |
|
- dpo |
|
- generated_from_trainer |
|
base_model: HuggingFaceTB/SmolLM-360M-Instruct |
|
model-index: |
|
- name: SmolLM-1.7B-Instruct-dpo-16k |
|
results: [] |
|
language: |
|
- en |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# SmolLM-1.7B-Instruct-dpo-16k |
|
|
|
This model is a fine-tuned version of [HuggingFaceTB/SmolLM-360M-Instruct](https://huggingface.co./HuggingFaceTB/SmolLM-360M-Instruct) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8854 |
|
- Rewards/chosen: 0.0056 |
|
- Rewards/rejected: 0.3516 |
|
- Rewards/accuracies: 0.0326 |
|
- Rewards/margins: -0.3460 |
|
- Logps/rejected: -470.7809 |
|
- Logps/chosen: -546.0043 |
|
- Logits/rejected: 0.3165 |
|
- Logits/chosen: 0.6158 |
|
|
|
## 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-06 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 2 |
|
- num_epochs: 6 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
|
|:-------------:|:------:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
|
| 0.5228 | 0.9999 | 3368 | 0.8697 | 0.0208 | 0.3405 | 0.0348 | -0.3197 | -470.8920 | -545.8519 | 0.3270 | 0.6295 | |
|
| 0.4508 | 2.0 | 6737 | 0.8870 | 0.0130 | 0.3621 | 0.0228 | -0.3491 | -470.6755 | -545.9296 | 0.2662 | 0.5778 | |
|
| 0.4451 | 2.9999 | 10105 | 0.8871 | 0.0057 | 0.3546 | 0.0337 | -0.3489 | -470.7502 | -546.0029 | 0.2855 | 0.5938 | |
|
| 0.4447 | 4.0 | 13474 | 0.8869 | 0.0098 | 0.3588 | 0.0196 | -0.3490 | -470.7085 | -545.9620 | 0.3198 | 0.6222 | |
|
| 0.4446 | 4.9999 | 16842 | 0.8870 | 0.0065 | 0.3551 | 0.0391 | -0.3486 | -470.7452 | -545.9945 | 0.3097 | 0.6124 | |
|
| 0.4448 | 5.9991 | 20208 | 0.8854 | 0.0056 | 0.3516 | 0.0326 | -0.3460 | -470.7809 | -546.0043 | 0.3165 | 0.6158 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- Pytorch 2.2.0 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
