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I follow the description from prosparse-7B and test the Acc on MMLU with this repo. MMLU average Acc is 41.69 but paper reports 45.21.
Here is one sample eval configuration:
{ "task_name": "mmlu_high-school-microeconomics_gen", "path": "datasets/mmlu/data/high-school-microeconomics.jsonl", "description": "The following are multiple choice questions (with answers) about high_school_microeconomics.\n\n", "transform": "datasets/mmlu/transform_gen_v1.py", "fewshot": 5, "generate": { "method": "generate", "params": "" }, "postprocess": "", "metric": { "accuracy": { "evaluation": { "type": "prefix_match" } } } }
generation_config:
{ "bos_token_id": 1, "do_sample": true, "eos_token_id": 2, "pad_token_id": 0, "temperature": 0.6, "max_new_tokens": 10, "top_p": 0.9, "transformers_version": "4.31.0.dev0" }
prosparse-7B configuration:
{ "_name_or_path": "SparseLLM/prosparse-llama-2-7b", "architectures": [ "SparseLlamaForCausalLM" ], "auto_map": { "AutoConfig": "configuration_sparsellama.SparseLlamaConfig", "AutoModel": "modeling_sparsellama.SparseLlamaForCausalLM", "AutoModelForCausalLM": "modeling_sparsellama.SparseLlamaForCausalLM" }, "bos_token_id": 1, "eos_token_id": 2, "hidden_act": "relu", "hidden_act_param": 0.01, "hidden_size": 4096, "initializer_range": 0.02, "intermediate_size": 11008, "max_position_embeddings": 4096, "model_type": "sparsellama", "num_attention_heads": 32, "num_hidden_layers": 32, "num_key_value_heads": 32, "pad_token_id": 0, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": null, "tie_word_embeddings": false, "torch_dtype": "bfloat16", "transformers_version": "4.31.0.dev0", "use_cache": true, "vocab_size": 32000, "max_length": 4096 }
The text was updated successfully, but these errors were encountered:
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I follow the description from prosparse-7B and test the Acc on MMLU with this repo. MMLU average Acc is 41.69 but paper reports 45.21.
Here is one sample eval configuration:
generation_config:
prosparse-7B configuration:
The text was updated successfully, but these errors were encountered: