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README.md
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---
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: NewEden_nemo-chatml
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model-index:
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- name: 12b-out-rslora-SE
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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: `0.5.0`
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```yaml
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## model
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base_model: NewEden_nemo-chatml
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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## qlora COPE
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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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## data
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datasets:
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- path: AquaV/c2-sharegpt-advanced-prefills-filtered
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type: danchat-advanced
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- path: AquaV/c1-sharegpt-advanced-prefills-filtered
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type: danchat-advanced
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- path: AquaV/rainy-sharegpt-advanced-prefills-filtered
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type: danchat-advanced
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- path: anthracite-core/Gryphe-Opus-Charcard-Roleplay
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type: danchat-advanced
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- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
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type: danchat-advanced
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- path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
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type: danchat-advanced
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- path: anthracite-org/nopm_claude_writing_fixed
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type: danchat-advanced
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- path: anthracite-org/kalo_opus_misc_240827
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type: danchat-advanced
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- path: anthracite-org/kalo_misc_part2
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type: danchat-advanced
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- path: NewEden/Claude-Instruct-2.7K
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type: danchat-advanced
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- path: NewEden/Claude-Instruct-5K
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type: danchat-advanced
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shuffle_merged_datasets: true
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dataset_prepared_path: dataset_prepared
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val_set_size: 0.02
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output_dir: 12b-out-rslora-SE
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## LIGGER
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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_layer_norm: true
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liger_glu_activation: true
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liger_fused_linear_cross_entropy: true
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## CTX settings
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sequence_len: 16384
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sample_packing: true
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eval_sample_packing: true
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pad_to_sequence_len: true
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## Lora
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adapter: lora
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lora_model_dir:
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lora_r: 128
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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peft_use_rslora: true
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lora_modules_to_save:
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- embed_tokens
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- lm_head
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## WandB
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wandb_project: SE-mag-12B
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wandb_entity:
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wandb_watch:
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wandb_name: daring-mango
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wandb_log_model:
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## evals
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evals_per_epoch: 4
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eval_table_size:
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eval_max_new_tokens: 128
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## hoe params
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gradient_accumulation_steps: 4
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micro_batch_size: 1
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num_epochs: 2
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optimizer: paged_ademamix_8bit
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# optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 2.83e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: unsloth
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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s2_attention:
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warmup_steps: 40
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saves_per_epoch: 2
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debug:
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## for ademiamix
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json
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## for adamw
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# deepspeed: ./deepspeed_configs/zero3_bf16.json
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weight_decay: 0.01
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <pad>
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```
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</details><br>
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# 12b-out-rslora-SE
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0001
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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: 2.83e-05
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- train_batch_size: 1
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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: 4
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- total_eval_batch_size: 4
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- optimizer: Use OptimizerNames.PAGED_ADEMAMIX_8BIT and the args are:
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No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 40
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 5.6935 | 0.0015 | 1 | 1.3433 |
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| 4.2418 | 0.2498 | 166 | 1.0758 |
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| 4.3565 | 0.4996 | 332 | 1.0486 |
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| 4.0471 | 0.7494 | 498 | 1.0297 |
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| 4.4088 | 0.9992 | 664 | 1.0146 |
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| 3.596 | 1.2494 | 830 | 1.0110 |
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| 3.4738 | 1.4992 | 996 | 1.0045 |
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| 3.6522 | 1.7491 | 1162 | 1.0010 |
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| 3.2321 | 1.9989 | 1328 | 1.0001 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.1
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- Pytorch 2.3.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.3
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