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---
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library_name: peft
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license: apache-2.0
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base_model: Qwen/Qwen2.5-7B
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tags:
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- axolotl
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- generated_from_trainer
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datasets:
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- sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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model-index:
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- name: reasoning-v0.2-qwen2.5-7b
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.7.0`
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```yaml
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base_model: Qwen/Qwen2.5-7B
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hub_model_id: sumukshashidhar-testing/reasoning-v0.2-qwen2.5-7b
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trust_remote_code: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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bf16: true
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hf_use_auth_token: true
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_glu_activation: true
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liger_layer_norm: true
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liger_fused_linear_cross_entropy: true
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save_safetensors:
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datasets:
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- path: sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data
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type: completion
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field: text
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dataset_prepared_path: .axolotl_cache_data/reasoning-rerankers
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shuffle_merged_datasets: true
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# dataset_exact_deduplication: true
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val_set_size: 0.05
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output_dir: /scratch/reasoning-reankers/reasoning-v0.1-qwen2.5-7b
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push_dataset_to_hub: sumukshashidhar-testing/reasoning-rerankers-relevance-sft-data-in-progress
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sequence_length: 2048
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sample_packing: true
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pad_to_sequence_len: true
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adapter: lora
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lora_r: 256
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lora_alpha: 32
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lora_dropout: 0.05
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peft_use_rslora: true
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lora_target_linear: true
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gradient_accumulation_steps: 1
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micro_batch_size: 32
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eval_batch_size: 1
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num_epochs: 3
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learning_rate: 5e-4
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warmup_ratio: 0.05
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evals_per_epoch: 2
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saves_per_epoch: 2
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gradient_checkpointing: true
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lr_scheduler: cosine
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optimizer: paged_adamw_8bit
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profiler_steps: 100
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save_safetensors: true
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train_on_inputs: true
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wandb_project: reasoning-rerankers
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wandb_name: rr-qwen-7b
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deepspeed: zero1.json
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```
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</details><br>
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# reasoning-v0.2-qwen2.5-7b
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.4119
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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- train_batch_size: 32
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 256
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- total_eval_batch_size: 8
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 49
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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0.0030 | 1 | 2.2497 |
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| 0.51 | 0.5 | 166 | 0.7306 |
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| 0.2733 | 1.0 | 332 | 0.5004 |
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| 0.1938 | 1.5 | 498 | 0.4445 |
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| 0.1783 | 2.0 | 664 | 0.4152 |
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| 0.1446 | 2.5 | 830 | 0.4147 |
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| 0.1424 | 3.0 | 996 | 0.4119 |
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.48.3
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- Pytorch 2.4.0
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- Datasets 3.2.0
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- Tokenizers 0.21.1 |
