---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-32B
tags:
- generated_from_trainer
datasets:
- StudyPal/education
model-index:
- name: outputs/qwen25-croatian-education
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.8.0.dev0`
```yaml
base_model: Qwen/Qwen2.5-32B
datasets:
  - path: StudyPal/education
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: from
      content: value
output_dir: ./outputs/qwen25-croatian-education

sequence_len: 1024
adapter: lora

lora_r: 32
lora_alpha: 64
lora_dropout: 0.05
lora_target_modules:
  - q_proj
  - v_proj
  - k_proj
  - o_proj
  - gate_proj
  - down_proj
  - up_proj

gradient_accumulation_steps: 8
micro_batch_size: 2
max_steps: 1500
optimizer: paged_adamw_8bit
learning_rate: 0.0001
load_in_4bit: true
train_on_inputs: false
bf16: auto

# Additional settings for 32B model
trust_remote_code: true
bnb_4bit_quant_type: nf4
bnb_4bit_use_double_quant: true
bnb_4bit_compute_dtype: bfloat16
gradient_checkpointing: true
sample_packing: true
pad_to_sequence_len: true
val_set_size: 0.001
warmup_steps: 75
save_safetensors: true
flash_attention: true
dataloader_num_workers: 8
dataloader_pin_memory: true
eval_steps: 999999
eval_strategy: steps
save_steps: 750
logging_steps: 50

special_tokens:
  bos_token: "<|im_start|>"
  eos_token: "<|im_end|>"
  pad_token: "<|endoftext|>"
```

</details><br>

# outputs/qwen25-croatian-education

This model is a fine-tuned version of [Qwen/Qwen2.5-32B](https://huggingface.co/Qwen/Qwen2.5-32B) on the StudyPal/education dataset.

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT 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: 75
- training_steps: 1500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0003 | 1    | 1.4631          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0