kamrr
/

llama-3-8b_dolly_lora

+---
+license: llama3
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: meta-llama/Meta-Llama-3-8B
+model-index:
+- name: llama-3-8b_dolly_lora
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+[<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)
+<details><summary>See axolotl config</summary>
+axolotl version: `0.4.0`
+```yaml
+base_model: meta-llama/Meta-Llama-3-8B
+model_type: LlamaForCausalLM
+tokenizer_type: AutoTokenizer
+load_in_8bit: true
+load_in_4bit: false
+strict: false
+datasets:
+  - path: kareemamrr/databricks-dolly-15k-alpaca
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./outputs/lora-out
+sequence_len: 4096
+sample_packing: true
+pad_to_sequence_len: true
+adapter: lora
+lora_model_dir:
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+wandb_project: llama-3-8b-dolly-axolotl
+wandb_entity: kamr54
+hub_model_id: kareemamrr/llama-3-8b_dolly_lora
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 4
+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
+s2_attention:
+warmup_steps: 10
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+   pad_token: <|end_of_text|>
+```
+</details><br>
+# llama-3-8b_dolly_lora
+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.
+It achieves the following results on the evaluation set:
+- Loss: 1.5906
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 4
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.6347        | 0.0114 | 1    | 1.6104          |
+| 1.5831        | 0.2507 | 22   | 1.5513          |
+| 1.6087        | 0.5014 | 44   | 1.5421          |
+| 1.3508        | 0.7521 | 66   | 1.5383          |
+| 1.4055        | 1.0028 | 88   | 1.5344          |
+| 1.45          | 1.2279 | 110  | 1.5376          |
+| 1.3131        | 1.4786 | 132  | 1.5385          |
+| 1.1921        | 1.7293 | 154  | 1.5384          |
+| 1.4415        | 1.9801 | 176  | 1.5387          |
+| 1.3818        | 2.2051 | 198  | 1.5586          |
+| 1.3292        | 2.4558 | 220  | 1.5662          |
+| 1.4667        | 2.7066 | 242  | 1.5664          |
+| 1.3002        | 2.9573 | 264  | 1.5660          |
+| 1.3682        | 3.1852 | 286  | 1.5878          |
+| 1.2825        | 3.4359 | 308  | 1.5901          |
+| 1.3347        | 3.6866 | 330  | 1.5906          |
+### Framework versions
+- PEFT 0.10.0
+- Transformers 4.40.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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