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Training in progress, epoch 1

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README.md CHANGED
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- library_name: transformers
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- [More Information Needed]
 
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  ---
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+ base_model: EleutherAI/pythia-125m-deduped
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+ library_name: peft
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+ license: apache-2.0
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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: pythia-125m-gpt4-llm-cleaned
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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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+
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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: EleutherAI/pythia-125m-deduped
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+ load_in_8bit: false
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+ datasets:
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+ - path: teknium/GPT4-LLM-Cleaned
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+ type: alpaca
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+ dataset_prepared_path: ds-gpt4-llm-cleaned
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+ val_set_size: 0.05
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+ adapter: lora
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+ lora_model_dir:
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+ sequence_len: 512
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+ lora_r: 16
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+ lora_alpha: 32
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+ lora_dropout: 0.05
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+ lora_target_modules:
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+ - query_key_value
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+ lora_target_linear: true
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+ lora_fan_in_fan_out: true # pythia/GPTNeoX lora specific
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+ wandb_project:
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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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+ output_dir: ./outputs/lora-alpaca-pythia-125m
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+ gradient_accumulation_steps: 1
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+ micro_batch_size: 4
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+ num_epochs: 4
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+ learning_rate: 0.00001
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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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+ tf32: false
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+ float16: true
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+ gpu_memory_limit: 8GiB
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+ hub_model_id: jtatman/pythia-125m-gpt4-llm-cleaned
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+ lora_on_cpu: false
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+ early_stopping_patience:
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+ resume_from_checkpoint:
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+ local_rank:
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+ weight_decay: 0.1
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+ evals_per_epoch: 4
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+ logging_steps: 1
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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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+ # pythia-125m-gpt4-llm-cleaned
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+
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+ This model is a fine-tuned version of [EleutherAI/pythia-125m-deduped](https://huggingface.co/EleutherAI/pythia-125m-deduped) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.0568
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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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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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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: 100
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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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+ | 2.259 | 0.0001 | 1 | 3.3268 |
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+ | 1.9508 | 0.25 | 3190 | 2.0963 |
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+ | 2.0554 | 0.5 | 6380 | 2.0641 |
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+ | 2.0165 | 0.75 | 9570 | 2.0588 |
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+ | 1.9643 | 1.0 | 12760 | 2.0596 |
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+ | 2.4041 | 1.25 | 15950 | 2.0576 |
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+ | 1.7239 | 1.5 | 19140 | 2.0611 |
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+ | 1.6508 | 1.75 | 22330 | 2.0557 |
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+ | 1.8538 | 2.0 | 25520 | 2.0555 |
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+ | 2.1191 | 2.25 | 28710 | 2.0586 |
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+ | 2.4065 | 2.5 | 31900 | 2.0523 |
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+ | 1.8175 | 2.75 | 35090 | 2.0534 |
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+ | 2.3558 | 3.0 | 38280 | 2.0582 |
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+ | 1.8991 | 3.25 | 41470 | 2.0544 |
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+ | 2.1408 | 3.5 | 44660 | 2.0564 |
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+ | 2.0138 | 3.75 | 47850 | 2.0568 |
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+ | 2.0097 | 4.0 | 51040 | 2.0568 |
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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 4.41.2
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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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