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sumukshashidhar-testing
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reasoning-v0.2-qwen2.5-7b

PEFT
Safetensors
qwen2
axolotl
Generated from Trainer
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reasoning-v0.2-qwen2.5-7b
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---

library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-7B
tags:
- axolotl
- generated_from_trainer
datasets:
- sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
model-index:
- name: reasoning-v0.2-qwen2.5-7b
  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: `0.7.0`
```yaml

base_model: Qwen/Qwen2.5-7B

hub_model_id: sumukshashidhar-testing/reasoning-v0.2-qwen2.5-7b

trust_remote_code: true



load_in_8bit: false

load_in_4bit: false

strict: false

bf16: true

hf_use_auth_token: true



plugins:

  - axolotl.integrations.liger.LigerPlugin

liger_rope: true

liger_rms_norm: true

liger_glu_activation: true

liger_layer_norm: true

liger_fused_linear_cross_entropy: true

save_safetensors:



datasets:

  - path: sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data

    type: completion

    field: text

dataset_prepared_path: .axolotl_cache_data/reasoning-rerankers

shuffle_merged_datasets: true

# dataset_exact_deduplication: true

val_set_size: 0.05

output_dir: /scratch/reasoning-reankers/reasoning-v0.1-qwen2.5-7b

push_dataset_to_hub: sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data-in-progress



sequence_length: 2048

sample_packing: true

pad_to_sequence_len: true



adapter: lora

lora_r: 256

lora_alpha: 32

lora_dropout: 0.05

peft_use_rslora: true

lora_target_linear: true



gradient_accumulation_steps: 1

micro_batch_size: 32

eval_batch_size: 1

num_epochs: 3

learning_rate: 5e-4

warmup_ratio: 0.05

evals_per_epoch: 2

saves_per_epoch: 2

gradient_checkpointing: true

lr_scheduler: cosine

optimizer: paged_adamw_8bit



profiler_steps: 100

save_safetensors: true

train_on_inputs: true

wandb_project: reasoning-rerankers

wandb_name: rr-qwen-7b

deepspeed: zero1.json



```

</details><br>

# reasoning-v0.2-qwen2.5-7b

This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4119

## 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: 0.0005

- train_batch_size: 32

- eval_batch_size: 1

- seed: 42

- distributed_type: multi-GPU
- num_devices: 8

- total_train_batch_size: 256
- total_eval_batch_size: 8

- 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: 49

- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0030 | 1    | 2.2497          |
| 0.51          | 0.5    | 166  | 0.7306          |
| 0.2733        | 1.0    | 332  | 0.5004          |
| 0.1938        | 1.5    | 498  | 0.4445          |
| 0.1783        | 2.0    | 664  | 0.4152          |
| 0.1446        | 2.5    | 830  | 0.4147          |
| 0.1424        | 3.0    | 996  | 0.4119          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.4.0
- Datasets 3.2.0
- Tokenizers 0.21.1