---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: ex19_qwen2.5-1.5b-1M-stack-16kcw
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ex19_qwen2.5-1.5b-1M-stack-16kcw

This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) on the stack_16k, the anghabench_16k_1 and the anghabench_16k_2 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.0003

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.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_ratio: 0.1
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step   | Validation Loss |
|:-------------:|:------:|:------:|:---------------:|
| 0.0037        | 0.1645 | 25000  | 0.0028          |
| 0.003         | 0.3289 | 50000  | 0.0017          |
| 0.002         | 0.4934 | 75000  | 0.0012          |
| 0.0002        | 0.6579 | 100000 | 0.0011          |
| 0.0011        | 0.8224 | 125000 | 0.0009          |
| 0.001         | 0.9868 | 150000 | 0.0007          |
| 0.0013        | 1.1513 | 175000 | 0.0005          |
| 0.0004        | 1.3158 | 200000 | 0.0005          |
| 0.0007        | 1.4802 | 225000 | 0.0004          |
| 0.0007        | 1.6447 | 250000 | 0.0004          |
| 0.0003        | 1.8092 | 275000 | 0.0003          |
| 0.0002        | 1.9736 | 300000 | 0.0003          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3