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README.md

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+---
+license: apache-2.0
+base_model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
+tags:
+- generated_from_trainer
+model-index:
+- name: workspace/out-mistral-2B
+  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
+adapter: null
+base_model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
+batch_size: 2
+bf16: auto
+dataset_prepared_path: null
+datasets:
+- ds_type: json
+  path: /workspace/data.jsonl
+  type: context_qa.load_v2
+debug: null
+deepspeed: null
+early_stopping_patience: null
+evals_per_epoch: 4
+flash_attention: null
+fp16: null
+fsdp: null
+fsdp_config: null
+gptq_groupsize: null
+gptq_model_v1: null
+gradient_checkpointing: true
+group_by_length: false
+learning_rate: 1.0e-05
+local_rank: null
+logging_steps: 1
+lora_alpha: 32
+lora_dropout: 0.2
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 64
+lora_target_linear: true
+lora_target_modules: null
+lr_scheduler: cosine
+max_packed_sequence_len: null
+micro_batch_size: 1
+model_config:
+  output_router_logits: true
+model_type: MistralForCausalLM
+num_epochs: 4
+optimizer: adamw_bnb_8bit
+output_dir: /workspace/out-mistral-2B
+resume_from_checkpoint: null
+saves_per_epoch: 1
+sequence_len: 2048
+special_tokens:
+  bos_token: <s>
+  eos_token: <|im_end|>
+  pad_token: </s>
+tf32: true
+tokenizer_type: LlamaTokenizer
+torchdistx_path: null
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.05
+wandb_entity: null
+wandb_log_model: Nous-Hermes-2-Mistral-7B-DPO
+wandb_name: mistral
+wandb_project: Ultron-llama
+wandb_watch: null
+warmup_steps: 40
+weight_decay: 0.0
+xformers_attention: true
+
+```
+
+</details><br>
+
+# workspace/out-mistral-2B
+
+This model is a fine-tuned version of [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5036
+
+## 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: 1e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- total_eval_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 40
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.6411        | 0.02  | 1    | 0.4803          |
+| 0.5321        | 0.26  | 11   | 0.3867          |
+| 0.4077        | 0.51  | 22   | 0.3591          |
+| 0.4455        | 0.77  | 33   | 0.3995          |
+| 0.2921        | 1.02  | 44   | 0.4368          |
+| 0.3459        | 1.28  | 55   | 0.4884          |
+| 0.2768        | 1.53  | 66   | 0.4978          |
+| 0.4168        | 1.79  | 77   | 0.4808          |
+| 0.14          | 2.05  | 88   | 0.4547          |
+| 0.1132        | 2.3   | 99   | 0.4856          |
+| 0.1055        | 2.56  | 110  | 0.4916          |
+| 0.1385        | 2.81  | 121  | 0.4783          |
+| 0.0455        | 3.07  | 132  | 0.4677          |
+| 0.0211        | 3.33  | 143  | 0.4892          |
+| 0.0236        | 3.58  | 154  | 0.5016          |
+| 0.009         | 3.84  | 165  | 0.5036          |
+
+
+### Framework versions
+
+- Transformers 4.39.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.0