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  2. adapter_model.bin +3 -0
README.md ADDED
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+ ---
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+ license: llama3
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+ library_name: peft
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ base_model: meta-llama/Meta-Llama-3-8B
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+ model-index:
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+ - name: isafpr-llama3-lora
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/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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+ model_type: LlamaForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ load_in_8bit: false
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+ load_in_4bit: true
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+ strict: false
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+
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+ data_seed: 42
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+ seed: 42
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+
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+ datasets:
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+ - path: data/isaf_press_releases_ft.jsonl
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+ conversation: alpaca
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+ type: sharegpt
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+ dataset_prepared_path:
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+ val_set_size: 0.05
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+ output_dir: ./outputs/llama3/lora-out
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+ hub_model_id: strickvl/isafpr-llama3-lora
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+
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+ sequence_len: 2048
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len: true
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+
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+ adapter: lora
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+ lora_model_dir:
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+ lora_r: 32
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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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+ lora_modules_to_save:
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+ - embed_tokens
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+ - lm_head
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+
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+ wandb_project: isaf_pr_ft
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+ wandb_entity: strickvl
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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: 4
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+ micro_batch_size: 2
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+ num_epochs: 4
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.0002
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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: true
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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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+
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+ warmup_steps: 10
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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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+ saves_per_epoch: 1
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.0
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ pad_token: <|end_of_text|>
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+
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+ ```
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+
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+ </details><br>
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+
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+ # isafpr-llama3-lora
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0371
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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: 0.0002
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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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: 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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+ - num_epochs: 4
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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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+ | 2.0023 | 0.0173 | 1 | 2.0120 |
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+ | 0.0975 | 0.2597 | 15 | 0.0792 |
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+ | 0.0576 | 0.5195 | 30 | 0.0586 |
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+ | 0.0317 | 0.7792 | 45 | 0.0476 |
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+ | 0.0367 | 1.0390 | 60 | 0.0445 |
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+ | 0.0315 | 1.2078 | 75 | 0.0421 |
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+ | 0.0249 | 1.4675 | 90 | 0.0429 |
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+ | 0.0302 | 1.7273 | 105 | 0.0380 |
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+ | 0.0264 | 1.9870 | 120 | 0.0376 |
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+ | 0.0184 | 2.1515 | 135 | 0.0362 |
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+ | 0.0174 | 2.4113 | 150 | 0.0366 |
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+ | 0.0152 | 2.6710 | 165 | 0.0373 |
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+ | 0.016 | 2.9307 | 180 | 0.0361 |
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+ | 0.0128 | 3.0996 | 195 | 0.0361 |
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+ | 0.0172 | 3.3593 | 210 | 0.0369 |
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+ | 0.0086 | 3.6190 | 225 | 0.0371 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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