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README.md

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+---
+license: other
+base_model: Undi95/Meta-Llama-3-8B-hf
+tags:
+- generated_from_trainer
+model-index:
+- name: lora-out
+  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: Undi95/Meta-Llama-3-8B-hf
+model_type: LlamaForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: Pbug/bftest
+    type: sharegpt
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./lora-out
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 10
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 2e-5
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 100
+evals_per_epoch: 2
+eval_table_size:
+eval_sample_packing: False
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  pad_token: <|end_of_text|>
+```
+
+</details><br>
+
+# lora-out
+
+This model is a fine-tuned version of [Undi95/Meta-Llama-3-8B-hf](https://huggingface.co/Undi95/Meta-Llama-3-8B-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+
+## 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: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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: 100
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.5419        | 0.03  | 1    | nan             |
+| 2.5492        | 0.51  | 18   | nan             |
+| 2.434         | 1.01  | 36   | nan             |
+| 2.3504        | 1.5   | 54   | nan             |
+| 2.3643        | 2.0   | 72   | nan             |
+| 2.2834        | 2.48  | 90   | nan             |
+| 2.2383        | 2.98  | 108  | nan             |
+| 1.8786        | 3.47  | 126  | nan             |
+| 1.7963        | 3.98  | 144  | nan             |
+| 2.1853        | 4.47  | 162  | nan             |
+| 1.4333        | 4.98  | 180  | nan             |
+| 1.2058        | 5.46  | 198  | nan             |
+| 1.125         | 5.96  | 216  | nan             |
+| 0.809         | 6.44  | 234  | nan             |
+| 0.7118        | 6.94  | 252  | nan             |
+| 0.7175        | 7.44  | 270  | nan             |
+| 0.7341        | 7.94  | 288  | nan             |
+| 0.774         | 8.44  | 306  | nan             |
+| 0.6379        | 8.94  | 324  | nan             |
+| 0.562         | 9.41  | 342  | nan             |
+
+
+### Framework versions
+
+- Transformers 4.40.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0