---
library_name: transformers
license: bigcode-openrail-m
base_model: bigcode/starcoderbase-1b
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: 1.5923

## 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-05
- 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: 2000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5622        | 0.1992 | 100  | 1.2485          |
| 0.4589        | 0.3984 | 200  | 1.2126          |
| 0.4216        | 0.5976 | 300  | 1.2730          |
| 0.3743        | 0.7968 | 400  | 1.2278          |
| 0.3535        | 0.9960 | 500  | 1.2615          |
| 0.3011        | 1.1952 | 600  | 1.2960          |
| 0.2653        | 1.3944 | 700  | 1.3112          |
| 0.2734        | 1.5936 | 800  | 1.3759          |
| 0.2855        | 1.7928 | 900  | 1.3015          |
| 0.2528        | 1.9920 | 1000 | 1.3470          |
| 0.2083        | 2.1912 | 1100 | 1.4719          |
| 0.2318        | 2.3904 | 1200 | 1.4494          |
| 0.1935        | 2.5896 | 1300 | 1.4621          |
| 0.1809        | 2.7888 | 1400 | 1.4829          |
| 0.227         | 2.9880 | 1500 | 1.4911          |
| 0.1813        | 3.1873 | 1600 | 1.5903          |
| 0.1893        | 3.3865 | 1700 | 1.5906          |
| 0.1674        | 3.5857 | 1800 | 1.5916          |
| 0.1723        | 3.7849 | 1900 | 1.5921          |
| 0.1843        | 3.9841 | 2000 | 1.5923          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3