|
--- |
|
base_model: bigcode/starcoderbase-1b |
|
library_name: peft |
|
license: bigcode-openrail-m |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: peft-starcoder-finetuned |
|
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. --> |
|
|
|
# peft-starcoder-finetuned |
|
|
|
This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7358 |
|
|
|
## 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: 8 |
|
- total_train_batch_size: 16 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 1.1611 | 2.8470 | 100 | 0.6569 | |
|
| 0.845 | 5.6940 | 200 | 0.6875 | |
|
| 0.7272 | 8.5409 | 300 | 0.6951 | |
|
| 0.6726 | 11.3879 | 400 | 0.7098 | |
|
| 0.6433 | 14.2349 | 500 | 0.7211 | |
|
| 0.6115 | 17.0819 | 600 | 0.7309 | |
|
| 0.5989 | 19.9288 | 700 | 0.7325 | |
|
| 0.5888 | 22.7758 | 800 | 0.7352 | |
|
| 0.5828 | 25.6228 | 900 | 0.7355 | |
|
| 0.5851 | 28.4698 | 1000 | 0.7358 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.13.2 |
|
- Transformers 4.46.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.3 |
