QueryloopAI
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AlphaMonarch-laser

@@ -1,199 +1,335 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+license: cc-by-nc-4.0
+base_model: mlabonne/NeuralMonarch-7B
+tags:
+- generated_from_trainer
+- axolotl
+- mistral
+- instruct
+- finetune
+- chatml
+- gpt4
+- synthetic data
+- distillation
+model-index:
+- name: AlphaMonarch-laser
+  results: []
+datasets:
+- argilla/OpenHermes2.5-dpo-binarized-alpha
+language:
+- en
 library_name: transformers
+pipeline_tag: text-generation
 ---
+<!-- 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. -->
+# AlphaMonarch-laser
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64e380b2e12618b261fa6ba0/62S_ExHO6NKCM3NhPDrds.jpeg)
+AlphaMonarch-laser is a DPO fine-tuned of [mlabonne/NeuralMonarch-7B](https://huggingface.co/mlabonne/NeuralMonarch-7B/) using the [argilla/OpenHermes2.5-dpo-binarized-alpha](https://huggingface.co/datasets/argilla/OpenHermes2.5-dpo-binarized-alpha) preference dataset but achieves better performance then [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B/) using  LaserQLoRA. I have fine-tuned this model only on half of the projections, but have achieved better results as compared to the version released by Maximme Labonne. I have trained this model for 1080 steps.
+AlphaMonarch-laser is ranking 1 on YALL - [Yet Another LLM Leaderboard](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64e380b2e12618b261fa6ba0/Jgxw1FZRx7nNAdSh7nYt1.png)
+## 🏆 Evaluation results
+# Nous Benchmark
+### AGIEVAL
+| Task                            | Version | Metric       | Value  | StdErr |
+|---------------------------------|---------|--------------|--------|--------|
+| agieval_aqua_rat                |     0   | acc          | 28.35% | 2.83%  |
+| agieval_aqua_rat                |     0   | acc_norm     | 26.38% | 2.77%  |
+| agieval_logiqa_en               |     0   | acc          | 38.25% | 1.91%  |
+| agieval_logiqa_en               |     0   | acc_norm     | 38.10% | 1.90%  |
+| agieval_lsat_ar                 |     0   | acc          | 23.91% | 2.82%  |
+| agieval_lsat_ar                 |     0   | acc_norm     | 23.48% | 2.80%  |
+| agieval_lsat_lr                 |     0   | acc          | 52.75% | 2.21%  |
+| agieval_lsat_lr                 |     0   | acc_norm     | 53.92% | 2.21%  |
+| agieval_lsat_rc                 |     0   | acc          | 66.91% | 2.87%  |
+| agieval_lsat_rc                 |     0   | acc_norm     | 67.29% | 2.87%  |
+| agieval_sat_en                  |     0   | acc          | 78.64% | 2.86%  |
+| agieval_sat_en                  |     0   | acc_norm     | 78.64% | 2.86%  |
+| agieval_sat_en_without_passage  |     0   | acc          | 45.15% | 3.48%  |
+| agieval_sat_en_without_passage  |     0   | acc_norm     | 44.17% | 3.47%  |
+| agieval_sat_math                |     0   | acc          | 33.18% | 3.18%  |
+| agieval_sat_math                |     0   | acc_norm     | 31.36% | 3.14%  |
+Average: 28.41%
+### GPT4ALL
+| Task         | Version | Metric   | Value | StdErr |
+|--------------|---------|----------|-------|--------|
+| arc_challenge| 0       | acc      | 66.30%| ± 1.38%|
+|              |         | acc_norm | 68.26%| ± 1.36%|
+| arc_easy     | 0       | acc      | 86.57%| ± 0.70%|
+|              |         | acc_norm | 80.81%| ± 0.81%|
+| boolq        | 1       | acc      | 87.16%| ± 0.59%|
+| hellaswag    | 0       | acc      | 69.60%| ± 0.46%|
+|              |         | acc_norm | 87.45%| ± 0.33%|
+| openbookqa   | 0       | acc      | 39.20%| ± 2.19%|
+|              |         | acc_norm | 49.60%| ± 2.24%|
+| piqa         | 0       | acc      | 83.03%| ± 0.88%|
+|              |         | acc_norm | 84.87%| ± 0.84%|
+| winogrande   | 0       | acc      | 81.06%| ± 1.10%|
+Average: 76.98%
+### TRUTHFUL-QA
+| Task          | Version | Metric | Value | StdErr |
+|---------------|---------|--------|-------|--------|
+| truthfulqa_mc |    1    |   mc1  | 63.04%| ± 1.69%|
+| truthfulqa_mc |    1    |   mc2  | 78.39%| ± 1.37%|
+Average: 70.71%
+### BIGBENCH
+| Task                                           | Version | Metric                | Value | StdErr             |
+|------------------------------------------------|---------|-----------------------|-------|--------------------|
+| bigbench_causal_judgement                      |    0    | multiple_choice_grade| 60.00%| ± 3.56%            |
+| bigbench_date_understanding                    |    0    | multiple_choice_grade| 62.06%| ± 2.53%            |
+| bigbench_disambiguation_qa                     |    0    | multiple_choice_grade| 54.26%| ± 3.11%            |
+| bigbench_geometric_shapes                      |    0    | multiple_choice_grade| 23.96%| ± 2.26%            |
+|                                                |         | exact_str_match       | 0.00% | ± 0.00%            |
+| bigbench_logical_deduction_five_objects        |    0    | multiple_choice_grade| 32.80%| ± 2.10%            |
+| bigbench_logical_deduction_seven_objects       |    0    | multiple_choice_grade| 23.86%| ± 1.61%            |
+| bigbench_logical_deduction_three_objects       |    0    | multiple_choice_grade| 59.33%| ± 2.84%            |
+| bigbench_movie_recommendation                  |    0    | multiple_choice_grade| 58.00%| ± 2.21%            |
+| bigbench_navigate                              |    0    | multiple_choice_grade| 56.00%| ± 1.57%            |
+| bigbench_reasoning_about_colored_objects       |    0    | multiple_choice_grade| 69.20%| ± 1.03%            |
+| bigbench_ruin_names                            |    0    | multiple_choice_grade| 55.36%| ± 2.35%            |
+| bigbench_salient_translation_error_detection   |    0    | multiple_choice_grade| 41.48%| ± 1.56%            |
+| bigbench_snarks                                |    0    | multiple_choice_grade| 73.48%| ± 3.29%            |
+| bigbench_sports_understanding                  |    0    | multiple_choice_grade| 76.06%| ± 1.36%            |
+| bigbench_temporal_sequences                    |    0    | multiple_choice_grade| 55.50%| ± 1.57%            |
+| bigbench_tracking_shuffled_objects_five_objects|    0    | multiple_choice_grade| 23.28%| ± 1.20%            |
+| bigbench_tracking_shuffled_objects_seven_objects|   0    | multiple_choice_grade| 19.37%| ± 0.94%            |
+| bigbench_tracking_shuffled_objects_three_objects|   0    | multiple_choice_grade| 59.33%| ± 2.84%            |
+Average: 55.37%
+# Openllm Benchmark
+|    Task     |Version| Metric |Value|   |Stderr|
+|-------------|------:|--------|----:|---|-----:|
+|arc_challenge|      0|acc     |70.12|±  |  1.30|
+|             |       |acc_norm|73.27|±  |  1.29|
+|hellaswag    |      0|acc     |71.80|±  |  0.44|
+|             |       |acc_norm|89.20|±  |  0.30|
+|gsm8k        |      0|acc     |66.77|±  |  1.2 |
+|winogrande   |      0|acc     |84.6 |±  |  1.0 |
+Average: 73.5%
+### TruthfulQA
+|    Task     |Version|Metric|Value|   |Stderr|
+|-------------|------:|------|----:|---|-----:|
+|truthfulqa_mc|      1|mc1   |62.79|±  |  1.69|
+|             |       |mc2   |77.90|±  |  1.37|
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-07
+- train_batch_size: 1
+- eval_batch_size: 8
+- 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
+- training_steps: 1080
+### 📝 Axolotl Configuration
+```yaml
+base_model: mlabonne/NeuralMonarch-7B
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+rl: dpo
+chat_template: chatml
+datasets:
+  - path: mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha
+    split: train
+    type: chatml.intel
+dataset_prepared_path:
+val_set_size: 0.01
+output_dir: ./out
+adapter: qlora
+lora_model_dir:
+sequence_len: 1800
+sample_packing: false
+pad_to_sequence_len: false
+lora_r: 16
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+ - layers.1.self_attn.q_proj
+ - layers.0.self_attn.q_proj
+ - layers.15.self_attn.q_proj
+ - layers.12.self_attn.q_proj
+ - layers.11.self_attn.q_proj
+ - layers.14.self_attn.q_proj
+ - layers.9.self_attn.q_proj
+ - layers.16.self_attn.q_proj
+ - layers.30.self_attn.q_proj
+ - layers.18.self_attn.q_proj
+ - layers.13.self_attn.q_proj
+ - layers.10.self_attn.q_proj
+ - layers.7.self_attn.q_proj
+ - layers.8.self_attn.q_proj
+ - layers.4.self_attn.q_proj
+ - layers.19.self_attn.q_proj
+ - layers.27.self_attn.k_proj
+ - layers.24.self_attn.k_proj
+ - layers.25.self_attn.k_proj
+ - layers.22.self_attn.k_proj
+ - layers.26.self_attn.k_proj
+ - layers.29.self_attn.k_proj
+ - layers.23.self_attn.k_proj
+ - layers.28.self_attn.k_proj
+ - layers.21.self_attn.k_proj
+ - layers.31.self_attn.k_proj
+ - layers.30.self_attn.k_proj
+ - layers.20.self_attn.k_proj
+ - layers.5.self_attn.k_proj
+ - layers.19.self_attn.k_proj
+ - layers.17.self_attn.k_proj
+ - layers.18.self_attn.k_proj
+ - layers.19.self_attn.v_proj
+ - layers.24.self_attn.v_proj
+ - layers.18.self_attn.v_proj
+ - layers.5.self_attn.v_proj
+ - layers.3.self_attn.v_proj
+ - layers.16.self_attn.v_proj
+ - layers.23.self_attn.v_proj
+ - layers.27.self_attn.v_proj
+ - layers.25.self_attn.v_proj
+ - layers.26.self_attn.v_proj
+ - layers.20.self_attn.v_proj
+ - layers.6.self_attn.v_proj
+ - layers.15.self_attn.v_proj
+ - layers.17.self_attn.v_proj
+ - layers.29.self_attn.v_proj
+ - layers.22.self_attn.v_proj
+ - layers.12.self_attn.o_proj
+ - layers.9.self_attn.o_proj
+ - layers.14.self_attn.o_proj
+ - layers.0.self_attn.o_proj
+ - layers.6.self_attn.o_proj
+ - layers.8.self_attn.o_proj
+ - layers.10.self_attn.o_proj
+ - layers.11.self_attn.o_proj
+ - layers.13.self_attn.o_proj
+ - layers.24.self_attn.o_proj
+ - layers.7.self_attn.o_proj
+ - layers.15.self_attn.o_proj
+ - layers.5.self_attn.o_proj
+ - layers.17.self_attn.o_proj
+ - layers.25.self_attn.o_proj
+ - layers.4.self_attn.o_proj
+ - layers.31.mlp.gate_proj
+ - layers.30.mlp.gate_proj
+ - layers.4.mlp.gate_proj
+ - layers.3.mlp.gate_proj
+ - layers.29.mlp.gate_proj
+ - layers.28.mlp.gate_proj
+ - layers.6.mlp.gate_proj
+ - layers.27.mlp.gate_proj
+ - layers.5.mlp.gate_proj
+ - layers.26.mlp.gate_proj
+ - layers.25.mlp.gate_proj
+ - layers.7.mlp.gate_proj
+ - layers.2.mlp.gate_proj
+ - layers.24.mlp.gate_proj
+ - layers.23.mlp.gate_proj
+ - layers.10.mlp.gate_proj
+ - layers.6.mlp.up_proj
+ - layers.4.mlp.up_proj
+ - layers.5.mlp.up_proj
+ - layers.27.mlp.up_proj
+ - layers.25.mlp.up_proj
+ - layers.26.mlp.up_proj
+ - layers.17.mlp.up_proj
+ - layers.24.mlp.up_proj
+ - layers.7.mlp.up_proj
+ - layers.10.mlp.up_proj
+ - layers.3.mlp.up_proj
+ - layers.11.mlp.up_proj
+ - layers.23.mlp.up_proj
+ - layers.9.mlp.up_proj
+ - layers.14.mlp.up_proj
+ - layers.18.mlp.up_proj
+ - layers.19.mlp.down_proj
+ - layers.20.mlp.down_proj
+ - layers.18.mlp.down_proj
+ - layers.21.mlp.down_proj
+ - layers.29.mlp.down_proj
+ - layers.1.mlp.down_proj
+ - layers.22.mlp.down_proj
+ - layers.28.mlp.down_proj
+ - layers.23.mlp.down_proj
+ - layers.30.mlp.down_proj
+ - layers.17.mlp.down_proj
+ - layers.4.mlp.down_proj
+ - layers.2.mlp.down_proj
+ - layers.15.mlp.down_proj
+ - layers.5.mlp.down_proj
+wandb_project: axolotl
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 1
+optimizer: paged_adamw_32bit
+lr_scheduler: cosine
+learning_rate: 5e-7
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: true
+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: 1
+eval_table_size:
+eval_table_max_new_tokens: 128
+save_steps: 1080
+max_steps: 1080
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+```
+### Framework versions
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu118
+- Datasets 2.17.0
+- Tokenizers 0.15.0
+- axolotl: 0.4.0
+[<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)