File size: 4,012 Bytes
4b41fd4 99b9470 4b41fd4 99b9470 4b41fd4 99b9470 4b41fd4 99b9470 4b41fd4 d7394bd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 |
---
license: openrail
tags:
- generated_from_trainer
model-index:
- name: santacoder-finetuned-the-stack-swift
results: []
datasets:
- bigcode/the-stack-dedup
language:
- code
pipeline_tag: text-generation
---
<!-- 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. -->
# SantaCoder 🎅 fine-tuned on Swift 🍏
This model is a fine-tuned version of [bigcode/santacoder](https://huggingface.co/bigcode/santacoder) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8353
## Model description
The [SantaCoder](https://huggingface.co/bigcode/santacoder) models are a series of 1.1B parameter models trained on the Python, Java, and JavaScript subset of [The Stack (v1.1)](https://huggingface.co/datasets/bigcode/the-stack) (which excluded opt-out requests).
The main model uses [Multi Query Attention](https://arxiv.org/abs/1911.02150), was trained using near-deduplication and comment-to-code ratio as filtering criteria and using the [Fill-in-the-Middle objective](https://arxiv.org/abs/2207.14255).
In addition, there are several models that were trained on datasets with different filter parameters and with architecture and objective variations.
## Intended uses & limitations
More information needed
## Training and evaluation data
The Stack contains over 6TB of permissively-licensed source code files covering 358 programming languages. The dataset was created as part of the [BigCode Project](https://www.bigcode-project.org/), an open scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs). The Stack serves as a pre-training dataset for Code LLMs, i.e., code-generating AI systems which enable the synthesis of programs from natural language descriptions as well as other from code snippets. **This is the near-deduplicated version with 3TB data.**
## 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: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.1132 | 0.05 | 500 | 1.0496 |
| 1.0077 | 0.1 | 1000 | 1.0245 |
| 1.0109 | 0.15 | 1500 | 1.0111 |
| 1.1106 | 0.2 | 2000 | 1.0025 |
| 0.5083 | 0.25 | 2500 | 1.0163 |
| 0.2996 | 0.3 | 3000 | 1.0339 |
| 1.0745 | 0.35 | 3500 | 0.9682 |
| 1.0355 | 0.4 | 4000 | 0.9467 |
| 0.9156 | 0.45 | 4500 | 0.9229 |
| 0.8834 | 0.5 | 5000 | 0.9199 |
| 0.6363 | 0.55 | 5500 | 0.9048 |
| 0.8771 | 0.6 | 6000 | 0.8899 |
| 1.9208 | 0.65 | 6500 | 0.8727 |
| 0.8816 | 0.7 | 7000 | 0.8633 |
| 0.8918 | 0.75 | 7500 | 0.8543 |
| 0.8714 | 0.8 | 8000 | 0.8454 |
| 0.9486 | 0.85 | 8500 | 0.8402 |
| 1.0609 | 0.9 | 9000 | 0.8364 |
| 0.9124 | 0.95 | 9500 | 0.8356 |
| 0.9743 | 1.0 | 10000 | 0.8353 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
### Citation
```
@misc {manuel_romero_2023,
author = { {Manuel Romero} },
title = { santacoder-finetuned-the-stack-swift (Revision 99b9470) },
year = 2023,
url = { https://huggingface.co/mrm8488/santacoder-finetuned-the-stack-swift },
doi = { 10.57967/hf/0348 },
publisher = { Hugging Face }
}
```
|