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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: transformers
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+ license: llama3
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+ base_model: meta-llama/Meta-Llama-3-8B
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ model-index:
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+ - name: L3-Pneuma-8B
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+ results: []
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+ ---
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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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+
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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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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: meta-llama/Meta-Llama-3-8B
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+
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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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+
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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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+
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+ datasets:
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+ - path: Kquant03/Sandevistan_Reformat
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+ type: customllama3_stan
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0.05
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+ output_dir: ./outputs/out
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+ max_steps: 80000
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+
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+ fix_untrained_tokens: true
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+
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+ sequence_len: 4096
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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+ wandb_project: Pneuma
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name:
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 16
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+ micro_batch_size: 8
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+ num_epochs: 1
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+ optimizer: paged_adamw_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.00001
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+ max_grad_norm: 1
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+
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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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+
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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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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+ eval_sample_packing: false
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+
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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_swiglu: true
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+ liger_fused_linear_cross_entropy: true
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+
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+ hub_model_id: Replete-AI/L3-Pneuma-8B
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+ hub_strategy: every_save
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+
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+ warmup_steps: 10
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+ evals_per_epoch: 3
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+ eval_table_size:
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+ saves_per_epoch: 3
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.1
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ bos_token: "<|begin_of_text|>"
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+ eos_token: "<|end_of_text|>"
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+ pad_token: "<|end_of_text|>"
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+ tokens:
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+ ```
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+
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+ </details><br>
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+
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+ # L3-Pneuma-8B
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+
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+ This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the [Sandevistan](https://huggingface.co/datasets/Replete-AI/Sandevistan) dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.7381
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 10
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+ - training_steps: 743
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 1.0378 | 0.0013 | 1 | 3.0437 |
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+ | 0.6816 | 0.3334 | 248 | 2.7341 |
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+ | 0.6543 | 0.6667 | 496 | 2.7381 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.20.1