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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: NeuralNovel/Neural-DPO |
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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: out |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: mistralai/Mistral-7B-v0.1 |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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rl: dpo |
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datasets: |
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- path: NeuralNovel/Neural-DPO |
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split: train |
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type: chatml.intel |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./out |
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sequence_len: 8192 |
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sample_packing: false |
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pad_to_sequence_len: true |
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eval_sample_packing: false |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: Neural-DPO |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 12 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 0 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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Creator: <a href="https://huggingface.co/NovoCode">NovoCode</a> |
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Community Organization: <a href="https://huggingface.co/ConvexAI">ConvexAI</a> |
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Discord: <a href="https://discord.gg/rJXGjmxqzS">Join us on Discord</a> |
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## Model description |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on [Neural-DPO](https://huggingface.co/datasets/NeuralNovel/Neural-DPO). |
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This model should excel at question answering across a rich array of subjects across a wide range of domains such as literature, scientific research, and theoretical inquiries. |
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## ExLlamaV2 Quants |
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ExLlamaV2 quants are available from [bartowski here](https://huggingface.co/bartowski/Mistral-NeuralDPO-v0.5-exl2) |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- training_steps: 1602 |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.0 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Novocoders__Mistral-NeuralDPO-v0.5) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |61.98| |
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|AI2 Reasoning Challenge (25-Shot)|65.44| |
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|HellaSwag (10-Shot) |84.66| |
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|MMLU (5-Shot) |62.56| |
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|TruthfulQA (0-shot) |42.43| |
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|Winogrande (5-shot) |80.27| |
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|GSM8k (5-shot) |36.54| |
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