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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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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: mistralai/Mistral-7B-v0.1
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+ model-index:
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+ - name: bts_mistral_7b_v3_32k
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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: `0.4.0`
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+ ```yaml
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+ base_model: mistralai/Mistral-7B-v0.1
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+ model_type: MistralForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+
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+ load_in_8bit: true
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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: jspr/bts-long-gpt-4-32k-0314-prompt
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+ type: alpaca
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+ dataset_prepared_path:
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+ val_set_size: 0.05
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+ output_dir: ./out
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+
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+ # using lora for lower cost
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+ adapter: lora
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+ lora_r: 8
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+ lora_alpha: 16
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+ lora_dropout: 0.05
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+ lora_target_modules:
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+ - q_proj
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+ - v_proj
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+
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+ sequence_len: 4096
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+ sample_packing: false # makes it faster but uses more memory
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+ pad_to_sequence_len: false
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+
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+ model_config:
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+ rope_scaling:
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+ type: linear
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+ factor: 8.0
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+
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+ hub_model_id: jspr/bts_mistral_7b_v3_32k
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+ hub_strategy: end
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+ hub_private_repo: true
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+
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+ wandb_project: bts
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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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+ # only 2 epochs because of small dataset
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+ gradient_accumulation_steps: 3
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+ micro_batch_size: 2
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+ num_epochs: 2
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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: true
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+ fp16: false
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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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+
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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: 16
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+ eval_sample_packing: false
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+ saves_per_epoch: 1
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+ debug:
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+
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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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+ bos_token: "<s>"
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+ eos_token: "</s>"
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+ unk_token: "<unk>"
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+ ```
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+
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+ </details><br>
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+
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+ # bts_mistral_7b_v3_32k
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.8543
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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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+ - gradient_accumulation_steps: 3
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+ - total_train_batch_size: 6
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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: 2
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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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+ | 2.0334 | 0.12 | 1 | 1.8829 |
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+ | 1.8664 | 0.25 | 2 | 1.8844 |
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+ | 1.813 | 0.5 | 4 | 1.8803 |
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+ | 1.8574 | 0.75 | 6 | 1.8751 |
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+ | 1.878 | 1.0 | 8 | 1.8680 |
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+ | 1.841 | 1.25 | 10 | 1.8599 |
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+ | 1.7903 | 1.5 | 12 | 1.8559 |
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+ | 1.808 | 1.75 | 14 | 1.8543 |
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+ | 1.9314 | 2.0 | 16 | 1.8543 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.9.0
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.0
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+ "v_proj",
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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