--- license: llama3.1 base_model: meta-llama/Meta-Llama-3.1-8B tags: - generated_from_trainer model-index: - name: workspace/axolotl/dolphin-2.9.4-llama3.1-8b results: [] ---
Evals ``` hf (pretrained=/workspace/axolotl/dolphin-2.9.4-llama3.1-8b-hf,dtype=bfloat16), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto (4) | Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |leaderboard |N/A |none | 0|acc |↑ |0.2926|± |0.0041| | | |none | 0|acc_norm |↑ |0.4513|± |0.0053| | | |none | 0|exact_match |↑ |0.0982|± |0.0079| | | |none | 0|inst_level_loose_acc |↑ |0.3825|± |N/A | | | |none | 0|inst_level_strict_acc |↑ |0.3597|± |N/A | | | |none | 0|prompt_level_loose_acc |↑ |0.2421|± |0.0184| | | |none | 0|prompt_level_strict_acc|↑ |0.2181|± |0.0178| | - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.4931|± |0.0061| | - leaderboard_bbh_boolean_expressions | 0|none | 3|acc_norm |↑ |0.8000|± |0.0253| | - leaderboard_bbh_causal_judgement | 0|none | 3|acc_norm |↑ |0.5615|± |0.0364| | - leaderboard_bbh_date_understanding | 0|none | 3|acc_norm |↑ |0.4520|± |0.0315| | - leaderboard_bbh_disambiguation_qa | 0|none | 3|acc_norm |↑ |0.6640|± |0.0299| | - leaderboard_bbh_formal_fallacies | 0|none | 3|acc_norm |↑ |0.5600|± |0.0315| | - leaderboard_bbh_geometric_shapes | 0|none | 3|acc_norm |↑ |0.3640|± |0.0305| | - leaderboard_bbh_hyperbaton | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306| | - 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 |↑ |0.4360|± |0.0314| | - leaderboard_bbh_logical_deduction_three_objects | 0|none | 3|acc_norm |↑ |0.6160|± |0.0308| | - leaderboard_bbh_movie_recommendation | 0|none | 3|acc_norm |↑ |0.7880|± |0.0259| | - leaderboard_bbh_navigate | 0|none | 3|acc_norm |↑ |0.5200|± |0.0317| | - leaderboard_bbh_object_counting | 0|none | 3|acc_norm |↑ |0.4520|± |0.0315| | - leaderboard_bbh_penguins_in_a_table | 0|none | 3|acc_norm |↑ |0.5205|± |0.0415| | - leaderboard_bbh_reasoning_about_colored_objects | 0|none | 3|acc_norm |↑ |0.5120|± |0.0317| | - leaderboard_bbh_ruin_names | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306| | - leaderboard_bbh_salient_translation_error_detection | 0|none | 3|acc_norm |↑ |0.4320|± |0.0314| | - leaderboard_bbh_snarks | 0|none | 3|acc_norm |↑ |0.5843|± |0.0370| | - leaderboard_bbh_sports_understanding | 0|none | 3|acc_norm |↑ |0.7040|± |0.0289| | - leaderboard_bbh_temporal_sequences | 0|none | 3|acc_norm |↑ |0.1440|± |0.0222| | - leaderboard_bbh_tracking_shuffled_objects_five_objects | 0|none | 3|acc_norm |↑ |0.1560|± |0.0230| | - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 0|none | 3|acc_norm |↑ |0.1320|± |0.0215| | - leaderboard_bbh_tracking_shuffled_objects_three_objects| 0|none | 3|acc_norm |↑ |0.2840|± |0.0286| | - leaderboard_bbh_web_of_lies | 0|none | 3|acc_norm |↑ |0.4840|± |0.0317| | - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.2903|± |0.0132| | - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.2980|± |0.0326| | - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.2839|± |0.0193| | - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.2946|± |0.0216| | - leaderboard_ifeval | 2|none | 0|inst_level_loose_acc |↑ |0.3825|± |N/A | | | |none | 0|inst_level_strict_acc |↑ |0.3597|± |N/A | | | |none | 0|prompt_level_loose_acc |↑ |0.2421|± |0.0184| | | |none | 0|prompt_level_strict_acc|↑ |0.2181|± |0.0178| | - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.1596|± |0.0209| | - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0488|± |0.0195| | - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0530|± |0.0196| | - leaderboard_math_hard |N/A |none | 4|exact_match |↑ |0.0982|± |0.0079| | - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0143|± |0.0071| | - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0455|± |0.0168| | - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.2591|± |0.0316| | - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0519|± |0.0192| | - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.2926|± |0.0041| | - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.3862|± |0.0173| | - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5280|± |0.0316| | - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.3594|± |0.0300| | - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.2720|± |0.0282| | Groups |Version|Filter|n-shot| Metric | |Value | |Stderr| |------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |leaderboard |N/A |none | 0|acc |↑ |0.2926|± |0.0041| | | |none | 0|acc_norm |↑ |0.4513|± |0.0053| | | |none | 0|exact_match |↑ |0.0982|± |0.0079| | | |none | 0|inst_level_loose_acc |↑ |0.3825|± |N/A | | | |none | 0|inst_level_strict_acc |↑ |0.3597|± |N/A | | | |none | 0|prompt_level_loose_acc |↑ |0.2421|± |0.0184| | | |none | 0|prompt_level_strict_acc|↑ |0.2181|± |0.0178| | - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.4931|± |0.0061| | - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.2903|± |0.0132| | - leaderboard_math_hard|N/A |none | 4|exact_match |↑ |0.0982|± |0.0079| | - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.3862|± |0.0173| ```
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See axolotl config axolotl version: `0.4.1` ```yaml base_model: meta-llama/Meta-Llama-3.1-8B model_type: LlamaForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false # load_in_4bit: true strict: false datasets: - path: /workspace/datasets/dolphin-2.9.4/dolphin201-sharegpt2.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: - input_layernorm - model.norm - post_attention_layernorm - self_attn.rotary_emb - ^lm_head.weight$ - ^model.embed_tokens.weight$ # mlp.down_proj layers - model.layers.1.mlp.down_proj - model.layers.0.mlp.down_proj - model.layers.30.mlp.down_proj - model.layers.2.mlp.down_proj - model.layers.21.mlp.down_proj - model.layers.22.mlp.down_proj - model.layers.29.mlp.down_proj - model.layers.5.mlp.down_proj - model.layers.4.mlp.down_proj - model.layers.20.mlp.down_proj - model.layers.23.mlp.down_proj - model.layers.19.mlp.down_proj - model.layers.3.mlp.down_proj - model.layers.17.mlp.down_proj - model.layers.6.mlp.down_proj - model.layers.31.mlp.down_proj # mlp.up_proj layers - model.layers.4.mlp.up_proj - model.layers.3.mlp.up_proj - model.layers.0.mlp.up_proj - model.layers.5.mlp.up_proj - model.layers.7.mlp.up_proj - model.layers.6.mlp.up_proj - model.layers.2.mlp.up_proj - model.layers.1.mlp.up_proj - model.layers.8.mlp.up_proj - model.layers.12.mlp.up_proj - model.layers.14.mlp.up_proj - model.layers.9.mlp.up_proj - model.layers.15.mlp.up_proj - model.layers.17.mlp.up_proj - model.layers.13.mlp.up_proj - model.layers.19.mlp.up_proj # self_attn.k_proj layers - model.layers.29.self_attn.k_proj - model.layers.25.self_attn.k_proj - model.layers.23.self_attn.k_proj - model.layers.28.self_attn.k_proj - model.layers.21.self_attn.k_proj - model.layers.19.self_attn.k_proj - model.layers.22.self_attn.k_proj - model.layers.20.self_attn.k_proj - model.layers.24.self_attn.k_proj - model.layers.31.self_attn.k_proj - model.layers.27.self_attn.k_proj - model.layers.26.self_attn.k_proj - model.layers.17.self_attn.k_proj - model.layers.11.self_attn.k_proj - model.layers.18.self_attn.k_proj - model.layers.14.self_attn.k_proj # self_attn.o_proj layers - model.layers.14.self_attn.o_proj - model.layers.7.self_attn.o_proj - model.layers.5.self_attn.o_proj - model.layers.11.self_attn.o_proj - model.layers.6.self_attn.o_proj - model.layers.24.self_attn.o_proj - model.layers.9.self_attn.o_proj - model.layers.13.self_attn.o_proj - model.layers.10.self_attn.o_proj - model.layers.12.self_attn.o_proj - model.layers.8.self_attn.o_proj - model.layers.25.self_attn.o_proj - model.layers.21.self_attn.o_proj - model.layers.23.self_attn.o_proj - model.layers.15.self_attn.o_proj - model.layers.16.self_attn.o_proj # self_attn.q_proj layers - model.layers.8.self_attn.q_proj - model.layers.13.self_attn.q_proj - model.layers.9.self_attn.q_proj - model.layers.14.self_attn.q_proj - model.layers.10.self_attn.q_proj - model.layers.11.self_attn.q_proj - model.layers.0.self_attn.q_proj - model.layers.15.self_attn.q_proj - model.layers.1.self_attn.q_proj - model.layers.6.self_attn.q_proj - model.layers.5.self_attn.q_proj - model.layers.7.self_attn.q_proj - model.layers.12.self_attn.q_proj - model.layers.16.self_attn.q_proj - model.layers.17.self_attn.q_proj - model.layers.26.self_attn.q_proj # self_attn.v_proj layers - model.layers.26.self_attn.v_proj - model.layers.17.self_attn.v_proj - model.layers.3.self_attn.v_proj - model.layers.28.self_attn.v_proj - model.layers.29.self_attn.v_proj - model.layers.21.self_attn.v_proj - model.layers.15.self_attn.v_proj - model.layers.16.self_attn.v_proj - model.layers.20.self_attn.v_proj - model.layers.25.self_attn.v_proj - model.layers.6.self_attn.v_proj - model.layers.23.self_attn.v_proj - model.layers.4.self_attn.v_proj - model.layers.1.self_attn.v_proj - model.layers.22.self_attn.v_proj - model.layers.14.self_attn.v_proj # mlp.gate_proj layers - model.layers.1.mlp.gate_proj - model.layers.2.mlp.gate_proj - model.layers.3.mlp.gate_proj - model.layers.4.mlp.gate_proj - model.layers.0.mlp.gate_proj - model.layers.25.mlp.gate_proj - model.layers.26.mlp.gate_proj - model.layers.5.mlp.gate_proj - model.layers.24.mlp.gate_proj - model.layers.28.mlp.gate_proj - model.layers.23.mlp.gate_proj - model.layers.27.mlp.gate_proj - model.layers.21.mlp.gate_proj - model.layers.22.mlp.gate_proj - model.layers.29.mlp.gate_proj - model.layers.20.mlp.gate_proj dataset_prepared_path: /workspace/axolotl/dolph-2.9.4-nemo-prepared val_set_size: 0.01 output_dir: /workspace/axolotl/dolphin-2.9.4-llama3.1-8b sequence_len: 8192 sample_packing: true pad_to_sequence_len: true wandb_project: dolphin-2.9.4-llama3.1-8b wandb_watch: wandb_run_id: wandb_log_model: gradient_accumulation_steps: 16 micro_batch_size: 2 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|>" bos_token: "<|begin_of_text|>" pad_token: "<|finetune_right_pad_id|>" 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 ```

# workspace/axolotl/dolphin-2.9.4-llama3.1-8b This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5655 ## 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: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 16 - total_train_batch_size: 256 - total_eval_batch_size: 16 - 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 | |:-------------:|:------:|:----:|:---------------:| | 0.5837 | 1.0180 | 1161 | 0.5814 | | 0.5525 | 2.0179 | 2322 | 0.5671 | | 0.5514 | 2.9624 | 3420 | 0.5655 | ### Framework versions - Transformers 4.44.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1