--- license: apache-2.0 tags: - generated_from_trainer - axolotl base_model: mistralai/Mistral-Nemo-Base-2407 datasets: - cognitivecomputations/Dolphin-2.9 - teknium/OpenHermes-2.5 - m-a-p/CodeFeedback-Filtered-Instruction - cognitivecomputations/dolphin-coder - cognitivecomputations/samantha-data - microsoft/orca-math-word-problems-200k - Locutusque/function-calling-chatml - internlm/Agent-FLAN model-index: - name: dolphin-2.9.3-mistral-nemo-12b results: - task: type: text-generation name: Text Generation dataset: name: ENEM Challenge (No Images) type: eduagarcia/enem_challenge split: train args: num_few_shot: 3 metrics: - type: acc value: 72.08 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BLUEX (No Images) type: eduagarcia-temp/BLUEX_without_images split: train args: num_few_shot: 3 metrics: - type: acc value: 62.45 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: OAB Exams type: eduagarcia/oab_exams split: train args: num_few_shot: 3 metrics: - type: acc value: 52.71 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Assin2 RTE type: assin2 split: test args: num_few_shot: 15 metrics: - type: f1_macro value: 93.08 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Assin2 STS type: eduagarcia/portuguese_benchmark split: test args: num_few_shot: 15 metrics: - type: pearson value: 80.83 name: pearson source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: FaQuAD NLI type: ruanchaves/faquad-nli split: test args: num_few_shot: 15 metrics: - type: f1_macro value: 81.28 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HateBR Binary type: ruanchaves/hatebr split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 85.85 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: PT Hate Speech Binary type: hate_speech_portuguese split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 73.07 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: tweetSentBR type: eduagarcia/tweetsentbr_fewshot split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 72.36 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b name: Open Portuguese LLM Leaderboard --- # Dolphin 2.9.3 Mistral Nemo 12b 🐬 Curated and trained by Eric Hartford and Cognitive Computations [![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/h3K4XGj2RH) Discord: https://discord.gg/h3K4XGj2RH Our appreciation for the sponsors of Dolphin 2.9.3: - [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xL40S node This model is based on mistralai/Mistral-Nemo-Base-2407, and is governed by the apache 2.0 license. The base model has 128K context, and our finetuning used 8192 sequence length. Dolphin 2.9.3 uses ChatML prompt template format. example: ``` <|im_start|>system You are Dolphin, a helpful AI assistant.<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` Dolphin-2.9.3 has a variety of instruction following, conversational, and coding skills. It also has initial agentic abilities and supports function calling. Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly. Dolphin is licensed according to apache 2.0 license. We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models. ## Evals
See evals ``` | Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |leaderboard |N/A |none | 0|acc |↑ |0.3437|± |0.0043| | | |none | 0|acc_norm |↑ |0.5076|± |0.0053| | | |none | 0|exact_match |↑ |0.0536|± |0.0061| | | |none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A | | | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A | | | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199| | | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186| | - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.5549|± |0.0061| | - leaderboard_bbh_boolean_expressions | 0|none | 3|acc_norm |↑ |0.8640|± |0.0217| | - leaderboard_bbh_causal_judgement | 0|none | 3|acc_norm |↑ |0.6417|± |0.0352| | - leaderboard_bbh_date_understanding | 0|none | 3|acc_norm |↑ |0.6080|± |0.0309| | - leaderboard_bbh_disambiguation_qa | 0|none | 3|acc_norm |↑ |0.6480|± |0.0303| | - leaderboard_bbh_formal_fallacies | 0|none | 3|acc_norm |↑ |0.5360|± |0.0316| | - leaderboard_bbh_geometric_shapes | 0|none | 3|acc_norm |↑ |0.5240|± |0.0316| | - leaderboard_bbh_hyperbaton | 0|none | 3|acc_norm |↑ |0.6440|± |0.0303| | - leaderboard_bbh_logical_deduction_five_objects | 0|none | 3|acc_norm |↑ |0.4600|± |0.0316| | - leaderboard_bbh_logical_deduction_seven_objects | 0|none | 3|acc_norm |↑ |0.4680|± |0.0316| | - leaderboard_bbh_logical_deduction_three_objects | 0|none | 3|acc_norm |↑ |0.7000|± |0.0290| | - leaderboard_bbh_movie_recommendation | 0|none | 3|acc_norm |↑ |0.8160|± |0.0246| | - leaderboard_bbh_navigate | 0|none | 3|acc_norm |↑ |0.6040|± |0.0310| | - leaderboard_bbh_object_counting | 0|none | 3|acc_norm |↑ |0.3680|± |0.0306| | - leaderboard_bbh_penguins_in_a_table | 0|none | 3|acc_norm |↑ |0.5548|± |0.0413| | - leaderboard_bbh_reasoning_about_colored_objects | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306| | - leaderboard_bbh_ruin_names | 0|none | 3|acc_norm |↑ |0.7440|± |0.0277| | - leaderboard_bbh_salient_translation_error_detection | 0|none | 3|acc_norm |↑ |0.5280|± |0.0316| | - leaderboard_bbh_snarks | 0|none | 3|acc_norm |↑ |0.6292|± |0.0363| | - leaderboard_bbh_sports_understanding | 0|none | 3|acc_norm |↑ |0.8040|± |0.0252| | - leaderboard_bbh_temporal_sequences | 0|none | 3|acc_norm |↑ |0.4680|± |0.0316| | - leaderboard_bbh_tracking_shuffled_objects_five_objects | 0|none | 3|acc_norm |↑ |0.2160|± |0.0261| | - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 0|none | 3|acc_norm |↑ |0.1160|± |0.0203| | - leaderboard_bbh_tracking_shuffled_objects_three_objects| 0|none | 3|acc_norm |↑ |0.3000|± |0.0290| | - leaderboard_bbh_web_of_lies | 0|none | 3|acc_norm |↑ |0.4880|± |0.0317| | - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.3146|± |0.0135| | - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.3182|± |0.0332| | - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.3187|± |0.0200| | - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.3080|± |0.0218| | - leaderboard_ifeval | 2|none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A | | | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A | | | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199| | | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186| | - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.0749|± |0.0150| | - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0244|± |0.0140| | - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0227|± |0.0130| | - leaderboard_math_hard |N/A |none | 4|exact_match |↑ |0.0536|± |0.0061| | - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0250|± |0.0093| | - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0390|± |0.0156| | - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.1295|± |0.0242| | - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0296|± |0.0146| | - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.3437|± |0.0043| | - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.4511|± |0.0178| | - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5880|± |0.0312| | - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.3438|± |0.0297| | - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.4240|± |0.0313| | Groups |Version|Filter|n-shot| Metric | |Value | |Stderr| |------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |leaderboard |N/A |none | 0|acc |↑ |0.3437|± |0.0043| | | |none | 0|acc_norm |↑ |0.5076|± |0.0053| | | |none | 0|exact_match |↑ |0.0536|± |0.0061| | | |none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A | | | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A | | | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199| | | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186| | - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.5549|± |0.0061| | - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.3146|± |0.0135| | - leaderboard_math_hard|N/A |none | 4|exact_match |↑ |0.0536|± |0.0061| | - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.4511|± |0.0178| ```

## Training [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml base_model: /workspace/models/Mistral-Nemo-Base-2407 model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false # load_in_4bit: true strict: false datasets: - path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl type: sharegpt conversation: chatml chat_template: chatml # adapter: qlora # lora_r: 128 # lora_alpha: 16 # lora_modules_to_save: [embed_tokens, lm_head] # lora_dropout: 0.05 # lora_target_linear: true unfrozen_parameters: - ^lm_head.weight$ - ^model.embed_tokens.weight$ - input_layernorm - model.norm - post_attention_layernorm - self_attn.rotary_emb # mlp.down_proj layers - model.layers.0.mlp.down_proj - model.layers.1.mlp.down_proj - model.layers.4.mlp.down_proj - model.layers.37.mlp.down_proj - model.layers.24.mlp.down_proj - model.layers.2.mlp.down_proj - model.layers.38.mlp.down_proj - model.layers.35.mlp.down_proj - model.layers.25.mlp.down_proj - model.layers.6.mlp.down_proj - model.layers.22.mlp.down_proj - model.layers.23.mlp.down_proj - model.layers.3.mlp.down_proj - model.layers.21.mlp.down_proj - model.layers.5.mlp.down_proj - model.layers.28.mlp.down_proj - model.layers.20.mlp.down_proj - model.layers.26.mlp.down_proj - model.layers.19.mlp.down_proj - model.layers.34.mlp.down_proj # mlp.gate_proj layers - model.layers.2.mlp.gate_proj - model.layers.1.mlp.gate_proj - model.layers.3.mlp.gate_proj - model.layers.5.mlp.gate_proj - model.layers.4.mlp.gate_proj - model.layers.35.mlp.gate_proj - model.layers.36.mlp.gate_proj - model.layers.37.mlp.gate_proj - model.layers.38.mlp.gate_proj - model.layers.34.mlp.gate_proj - model.layers.33.mlp.gate_proj - model.layers.8.mlp.gate_proj - model.layers.32.mlp.gate_proj - model.layers.6.mlp.gate_proj - model.layers.28.mlp.gate_proj - model.layers.26.mlp.gate_proj - model.layers.30.mlp.gate_proj - model.layers.23.mlp.gate_proj - model.layers.29.mlp.gate_proj - model.layers.27.mlp.gate_proj # mlp.up_proj layers - model.layers.3.mlp.up_proj - model.layers.4.mlp.up_proj - model.layers.6.mlp.up_proj - model.layers.2.mlp.up_proj - model.layers.5.mlp.up_proj - model.layers.8.mlp.up_proj - model.layers.10.mlp.up_proj - model.layers.9.mlp.up_proj - model.layers.7.mlp.up_proj - model.layers.0.mlp.up_proj - model.layers.17.mlp.up_proj - model.layers.15.mlp.up_proj - model.layers.22.mlp.up_proj - model.layers.18.mlp.up_proj - model.layers.16.mlp.up_proj - model.layers.11.mlp.up_proj - model.layers.21.mlp.up_proj - model.layers.23.mlp.up_proj - model.layers.20.mlp.up_proj - model.layers.27.mlp.up_proj # self_attn.k_proj layers - model.layers.30.self_attn.k_proj - model.layers.27.self_attn.k_proj - model.layers.25.self_attn.k_proj - model.layers.33.self_attn.k_proj - model.layers.26.self_attn.k_proj - model.layers.31.self_attn.k_proj - model.layers.35.self_attn.k_proj - model.layers.39.self_attn.k_proj - model.layers.22.self_attn.k_proj - model.layers.24.self_attn.k_proj - model.layers.21.self_attn.k_proj - model.layers.28.self_attn.k_proj - model.layers.23.self_attn.k_proj - model.layers.36.self_attn.k_proj - model.layers.20.self_attn.k_proj - model.layers.37.self_attn.k_proj - model.layers.29.self_attn.k_proj - model.layers.32.self_attn.k_proj - model.layers.16.self_attn.k_proj - model.layers.18.self_attn.k_proj # self_attn.o_proj layers - model.layers.7.self_attn.o_proj - model.layers.6.self_attn.o_proj - model.layers.9.self_attn.o_proj - model.layers.5.self_attn.o_proj - model.layers.27.self_attn.o_proj - model.layers.26.self_attn.o_proj - model.layers.4.self_attn.o_proj - model.layers.31.self_attn.o_proj - model.layers.8.self_attn.o_proj - model.layers.16.self_attn.o_proj - model.layers.3.self_attn.o_proj - model.layers.10.self_attn.o_proj - model.layers.18.self_attn.o_proj - model.layers.33.self_attn.o_proj - model.layers.17.self_attn.o_proj - model.layers.32.self_attn.o_proj - model.layers.30.self_attn.o_proj - model.layers.2.self_attn.o_proj - model.layers.15.self_attn.o_proj - model.layers.11.self_attn.o_proj # self_attn.q_proj layers - model.layers.14.self_attn.q_proj - model.layers.11.self_attn.q_proj - model.layers.15.self_attn.q_proj - model.layers.9.self_attn.q_proj - model.layers.8.self_attn.q_proj - model.layers.18.self_attn.q_proj - model.layers.12.self_attn.q_proj - model.layers.13.self_attn.q_proj - model.layers.19.self_attn.q_proj - model.layers.16.self_attn.q_proj - model.layers.10.self_attn.q_proj - model.layers.17.self_attn.q_proj - model.layers.7.self_attn.q_proj - model.layers.5.self_attn.q_proj - model.layers.20.self_attn.q_proj - model.layers.3.self_attn.q_proj - model.layers.26.self_attn.q_proj - model.layers.27.self_attn.q_proj - model.layers.28.self_attn.q_proj - model.layers.33.self_attn.q_proj # self_attn.v_proj layers - model.layers.27.self_attn.v_proj - model.layers.20.self_attn.v_proj - model.layers.24.self_attn.v_proj - model.layers.25.self_attn.v_proj - model.layers.30.self_attn.v_proj - model.layers.2.self_attn.v_proj - model.layers.23.self_attn.v_proj - model.layers.22.self_attn.v_proj - model.layers.26.self_attn.v_proj - model.layers.33.self_attn.v_proj - model.layers.37.self_attn.v_proj - model.layers.7.self_attn.v_proj - model.layers.4.self_attn.v_proj - model.layers.18.self_attn.v_proj - model.layers.31.self_attn.v_proj - model.layers.17.self_attn.v_proj - model.layers.35.self_attn.v_proj - model.layers.32.self_attn.v_proj - model.layers.21.self_attn.v_proj - model.layers.3.self_attn.v_proj dataset_prepared_path: /workspace/axolotl/dolph-2.9.3-nemo-prepared val_set_size: 0.01 output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-nemo sequence_len: 8192 sample_packing: true pad_to_sequence_len: true wandb_project: dolphin-2.9.3-Mistral-nemo wandb_watch: wandb_run_id: wandb_log_model: gradient_accumulation_steps: 16 micro_batch_size: 1 num_epochs: 3 optimizer: adamw_torch lr_scheduler: cosine learning_rate: 5e-6 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: 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: 4 eval_table_size: saves_per_epoch: 1 save_total_limit: 2 save_steps: debug: deepspeed: deepspeed_configs/zero3_bf16.json weight_decay: 0.1 special_tokens: eos_token: "<|im_end|>" pad_token: "" bos_token: "" unk_token: "" tokens: - "<|im_start|>" # fsdp: # - full_shard # - auto_wrap # fsdp_config: # fsdp_limit_all_gathers: true # fsdp_sync_module_states: true # fsdp_offload_params: true # fsdp_use_orig_params: false # fsdp_cpu_ram_efficient_loading: true # fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock # fsdp_state_dict_type: FULL_STATE_DICT # fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP # fsdp_sharding_strategy: FULL_SHARD # fsdp_forward_prefetch: false # fsdp_backward_prefetch: BACKWARD_PRE ```

[Visualize in Weights & Biases](https://wandb.ai/ehartford/dolphin-2.9.3-Mistral-nemo/runs/c23odyoj) # workspace/axolotl/dolphin-2.9.3-mistral-nemo This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5605 ## 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: 5e-06 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - total_eval_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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.5691 | 1.0162 | 983 | 0.5734 | | 0.5335 | 2.0174 | 1968 | 0.5609 | | 0.5297 | 2.9639 | 2901 | 0.5605 | ### Framework versions - Transformers 4.43.0.dev0 - Pytorch 2.2.2+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1 # Open Portuguese LLM Leaderboard Evaluation Results Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard) | Metric | Value | |--------------------------|---------| |Average |**74.86**| |ENEM Challenge (No Images)| 72.08| |BLUEX (No Images) | 62.45| |OAB Exams | 52.71| |Assin2 RTE | 93.08| |Assin2 STS | 80.83| |FaQuAD NLI | 81.28| |HateBR Binary | 85.85| |PT Hate Speech Binary | 73.07| |tweetSentBR | 72.36|