End of training

README.md

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+---
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: NousResearch/Llama-2-7b-hf
+model-index:
+- name: MathLlama-7b
+ 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: `0.3.0`
+```yaml
+base_model: NousResearch/Llama-2-7b-hf
+model_type: LlamaForCausalLM
+tokenizer_type: LlamaTokenizer
+is_llama_derived_model: true
+hub_model_id: MathLlama-7b
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+datasets:
+ - path: zorooo/Eval_Math_Derivatives
+ type: alpaca
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./qlora-out-2
+
+adapter: qlora
+lora_model_dir:
+
+sequence_len: 2048
+sample_packing: true
+pad_to_sequence_len: true
+
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules:
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project: axolotl_run_1_math_llama
+wandb_entity:
+wandb_watch:
+wandb_name: math_llama_run2
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 5
+optimizer: paged_adamw_32bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 100
+evals_per_epoch: 4
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+ bos_token: "<s>"
+ eos_token: "</s>"
+ unk_token: "<unk>"
+```
+
+</details><br>
+
+# MathLlama-7b
+
+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: 0.1580
+
+## 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: 100
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.952 | 0.04 | 1 | 0.9490 |
+| 0.9351 | 0.27 | 7 | 0.9474 |
+| 0.9431 | 0.54 | 14 | 0.9181 |
+| 0.8078 | 0.82 | 21 | 0.7671 |
+| 0.5693 | 1.06 | 28 | 0.5249 |
+| 0.309 | 1.33 | 35 | 0.3288 |
+| 0.2752 | 1.6 | 42 | 0.2607 |
+| 0.2406 | 1.87 | 49 | 0.2267 |
+| 0.2241 | 2.12 | 56 | 0.2068 |
+| 0.2212 | 2.39 | 63 | 0.1932 |
+| 0.1991 | 2.66 | 70 | 0.1842 |
+| 0.173 | 2.93 | 77 | 0.1738 |
+| 0.162 | 3.18 | 84 | 0.1711 |
+| 0.1357 | 3.46 | 91 | 0.1681 |
+| 0.15 | 3.73 | 98 | 0.1664 |
+| 0.1553 | 4.0 | 105 | 0.1610 |
+| 0.1263 | 4.25 | 112 | 0.1613 |
+| 0.132 | 4.52 | 119 | 0.1580 |
+
+
+### Framework versions
+
+- PEFT 0.7.2.dev0
+- Transformers 4.37.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

adapter_model.bin

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