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README.md ADDED
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+ ---
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+ base_model: meta-llama/Llama-2-7b-hf
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: out
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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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+ # out
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+
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+ This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2048
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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: 3.8e-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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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 64
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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: 3
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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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+ | 1.3782 | 0.01 | 1 | 1.4211 |
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+ | 1.1948 | 0.2 | 14 | 1.2273 |
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+ | 1.0953 | 0.4 | 28 | 1.2137 |
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+ | 1.1464 | 0.6 | 42 | 1.2099 |
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+ | 1.1481 | 0.81 | 56 | 1.2080 |
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+ | 1.0277 | 1.01 | 70 | 1.2022 |
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+ | 0.9344 | 1.21 | 84 | 1.2049 |
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+ | 1.1294 | 1.41 | 98 | 1.2033 |
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+ | 1.0933 | 1.61 | 112 | 1.2002 |
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+ | 0.987 | 1.81 | 126 | 1.1996 |
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+ | 0.9491 | 2.01 | 140 | 1.1972 |
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+ | 0.9673 | 2.22 | 154 | 1.2058 |
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+ | 0.99 | 2.42 | 168 | 1.2048 |
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+ | 0.9241 | 2.62 | 182 | 1.2049 |
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+ | 0.9204 | 2.82 | 196 | 1.2048 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.14.0
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+ {
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+ "_name_or_path": "meta-llama/Llama-2-7b-hf",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 11008,
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+ "max_position_embeddings": 4096,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 32,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.34.0.dev0",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
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+ base_model: meta-llama/Llama-2-7b-hf
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+ base_model_config: meta-llama/Llama-2-7b-hf
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+ model_type: MistralForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ is_mistral_derived_model: true
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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: timdettmers/openassistant-guanaco
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+ type: completion
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+ dataset_prepared_path:
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+ val_set_size: 0.1
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+ output_dir: ./out
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+
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+ sequence_len: 4096
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+ sample_packing: false
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+ pad_to_sequence_len: false
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+
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+ wandb_project: llama-neft-guanaco
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_run_id:
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 2
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+ micro_batch_size: 8
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+ num_epochs: 3
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+ optimizer: adamw_torch
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+ lr_scheduler: cosine
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+ learning_rate: 0.000038
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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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+ noisy_embedding_alpha: 5
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+
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+ warmup_steps: 10
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+ eval_steps: 0.0666666666
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+ save_steps:
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+ debug:
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+ deepspeed: deepspeed/zero2.json
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+ weight_decay: 0.0
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