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model_26f8a712

PEFT
Safetensors
qwen2
Generated from Trainer
4-bit precision
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model_26f8a712
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---

library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- generated_from_trainer
datasets:
- ugaoo/multimedqa_train
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
model-index:
- name: out/Qwen_Qwen2.5_7B_Instruct_ugaoo_multimedqa_train
  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/Qwen2.5-7B-Instruct

model_type: AutoModelForCausalLM

tokenizer_type: AutoTokenizer

trust_remote_code: true



load_in_8bit: false

load_in_4bit: true

strict: false



datasets:

  - path: ugaoo/multimedqa_train

    type: alpaca

val_set_size: 0

output_dir: ./out/Qwen_Qwen2.5_7B_Instruct_ugaoo_multimedqa_train



sequence_len: 4000

sample_packing: true

pad_to_sequence_len: true



adapter: qlora

lora_r: 256

lora_alpha: 512

lora_dropout: 0.05

lora_target_linear: true

lora_target_modules:

  - q_proj

  - k_proj

  - v_proj

  - o_proj

  - up_proj

  - down_proj

  - gate_proj

 

wandb_project: testsearch

wandb_entity:

wandb_watch: 

wandb_name: Qwen_Qwen2.5_7B_Instruct_ugaoo_multimedqa_train

wandb_log_model:



gradient_accumulation_steps: 3

micro_batch_size: 4

num_epochs: 6

optimizer: adamw_torch

lr_scheduler: cosine

learning_rate: 5e-6



train_on_inputs: false

group_by_length: false

bf16: auto

fp16: false

tf32: false



gradient_checkpointing: true

early_stopping_patience:

resume_from_checkpoint:

logging_steps: 1

xformers_attention:

flash_attention: true



warmup_steps: 100

evals_per_epoch: 6

eval_table_size:

saves_per_epoch: 1

debug:

deepspeed:

weight_decay: 0.0

fsdp:

fsdp_config:

save_total_limit: 6

```

</details><br>

# out/Qwen_Qwen2.5_7B_Instruct_ugaoo_multimedqa_train

This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the ugaoo/multimedqa_train 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU

- gradient_accumulation_steps: 3

- total_train_batch_size: 12
- 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_steps: 100

- num_epochs: 6.0

### Training results



### Framework versions

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