| --- |
| base_model: NousResearch/Llama-2-7b-hf |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: out |
| results: [] |
| --- |
| |
| ```yaml |
| base_model: NousResearch/Llama-2-7b-hf |
| model_type: LlamaForCausalLM |
| tokenizer_type: LlamaTokenizer |
| is_llama_derived_model: true |
| |
| load_in_8bit: false |
| load_in_4bit: false |
| strict: false |
| |
| datasets: |
| - path: CognitiveLab/FS_transcribe_summary_prompt |
| type: completion |
| dataset_prepared_path: last_run_prepared |
| val_set_size: 0.05 |
| output_dir: ./out |
| |
| sequence_len: 4096 |
| sample_packing: true |
| pad_to_sequence_len: true |
| |
| adapter: |
| lora_model_dir: |
| lora_r: |
| lora_alpha: |
| lora_dropout: |
| lora_target_linear: |
| lora_fan_in_fan_out: |
| |
| wandb_project: fireship-fft |
| wandb_entity: |
| wandb_watch: |
| wandb_name: |
| wandb_log_model: |
| |
| gradient_accumulation_steps: 4 |
| micro_batch_size: 4 |
| num_epochs: 1 |
| optimizer: adamw_bnb_8bit |
| lr_scheduler: cosine |
| learning_rate: 0.0002 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: auto |
| fp16: |
| tf32: false |
| |
| gradient_checkpointing: true |
| early_stopping_patience: |
| resume_from_checkpoint: |
| local_rank: |
| logging_steps: 1 |
| xformers_attention: |
| flash_attention: true |
| flash_attn_cross_entropy: false |
| flash_attn_rms_norm: true |
| flash_attn_fuse_qkv: false |
| flash_attn_fuse_mlp: true |
| |
| warmup_steps: 100 |
| evals_per_epoch: 4 |
| eval_table_size: |
| saves_per_epoch: 2 |
| debug: |
| deepspeed: #deepspeed_configs/zero2.json # multi-gpu only |
| weight_decay: 0.1 |
| fsdp: |
| fsdp_config: |
| special_tokens: |
| |
| ``` |
|
|
| </details><br> |
|
|
| # out |
|
|
| This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.8444 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0002 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 100 |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 2.1256 | 0.06 | 1 | 2.1641 | |
| | 2.1049 | 0.25 | 4 | 2.1254 | |
| | 1.9826 | 0.49 | 8 | 1.9868 | |
| | 1.8545 | 0.74 | 12 | 1.8779 | |
| | 1.8597 | 0.98 | 16 | 1.8444 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.36.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
|
|
