From 1a5dbce99f9e81d00a6d546308f3da6a826e2c81 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 8 Aug 2026 22:21:20 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: finnianx/michel-micro Source: Original Platform --- .gitattributes | 35 + README.md | 38 + config.json | 32 + generation_config.json | 12 + model.safetensors | 3 + results_2026-06-09T14-32-28.353831.json | 4664 +++ tokenizer.json | 39263 ++++++++++++++++++++++ tokenizer_config.json | 9 + training_args.bin | 3 + 9 files changed, 44059 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 results_2026-06-09T14-32-28.353831.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json create mode 100644 training_args.bin diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..a6344aa --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..7113b6e --- /dev/null +++ b/README.md @@ -0,0 +1,38 @@ +--- +datasets: +- HuggingFaceFW/fineweb-edu +- HuggingFaceTB/cosmopedia +- epfml/FineWeb2-HQ +language: +- en +--- +An ultra-tiny 28 million parameter model trained on 2.6 billion tokens using a custom dataset mixture. Context length of 1024 tokens. + +| Dataset | Weight | +|---|---| +| `HuggingFaceFW/fineweb-edu` | 50% | +| `epfml/FineWeb-HQ` | 30% | +| `HuggingFaceTB/cosmopedia` (stories split) | 20% | + +The tokenizer is a basic bpe tokenizer that was trained on a smaller subset of 80_000 samples of this same data mixture with a vocab size of 8000. + +This model has not undergone any post-training. + +This base model is best suited for fine-tuning on specific tasks. On its own, it is very limited, but it is a pretty flexible foundation for applications such as toxic comment detection or sentiment analysis. + +| Benchmark | Metric | Value | +|---|---|---| +| ARC-Challenge | Acc | 0.1980 | +| ARC-Challenge | Acc Norm | 0.2312 | +| ARC-Easy | Acc | 0.4091 | +| ARC-Easy | Acc Norm | 0.3859 | +| BoolQ | Acc | 0.5850 | +| HellaSwag | Acc | 0.2749 | +| HellaSwag | Acc Norm | 0.2823 | +| PIQA | Acc | 0.5963 | +| PIQA | Acc Norm | 0.5762 | +| WinoGrande | Acc | 0.4917 | +| WikiText | Word PPL | 86.6418 | +| WikiText | Byte PPL | 2.3034 | +| WikiText | Bits/Byte | 1.2037 | +| BLIMP (Avg) | Acc | 0.6975 | \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..38c2531 --- /dev/null +++ b/config.json @@ -0,0 +1,32 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 3, + "dtype": "float32", + "eos_token_id": 1, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 512, + "initializer_range": 0.02, + "intermediate_size": 1152, + "max_position_embeddings": 1024, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 8, + "num_hidden_layers": 10, + "num_key_value_heads": 2, + "pad_token_id": 2, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 10000.0, + "rope_type": "default" + }, + "tie_word_embeddings": true, + "transformers_version": "5.5.0", + "use_cache": false, + "vocab_size": 8000 +} diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..ee7cc22 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,12 @@ +{ + "_from_model_config": true, + "bos_token_id": 3, + "eos_token_id": [ + 1 + ], + "output_attentions": false, + "output_hidden_states": false, + "pad_token_id": 2, + "transformers_version": "5.5.0", + "use_cache": true +} diff --git a/model.safetensors b/model.safetensors new file mode 100644 index 0000000..df2dea1 --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:748176b83db44d8efba6331da174456f7f9828dcdbf03d2f46e014408538fde3 +size 113430352 diff --git a/results_2026-06-09T14-32-28.353831.json b/results_2026-06-09T14-32-28.353831.json new file mode 100644 index 0000000..a90ab03 --- /dev/null +++ b/results_2026-06-09T14-32-28.353831.json @@ -0,0 +1,4664 @@ +{ + "results": { + "winogrande": { + "name": "winogrande", + "alias": "winogrande", + "sample_len": 1267, + "acc,none": 0.49171270718232046, + "acc_stderr,none": 0.01405055532282417 + }, + "arc_easy": { + "name": "arc_easy", + "alias": "arc_easy", + "sample_len": 2376, + "acc,none": 0.4090909090909091, + "acc_stderr,none": 0.010088775152615642, + "acc_norm,none": 0.3859427609427609, + "acc_norm_stderr,none": 0.009989277329504026 + }, + "hellaswag": { + "name": "hellaswag", + "alias": "hellaswag", + "sample_len": 10042, + "acc,none": 0.2749452300338578, + 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"sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/tough_vs_raising_1.yaml" + } + }, + "blimp_tough_vs_raising_2": { + "task": "blimp_tough_vs_raising_2", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "tough_vs_raising_2", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/tough_vs_raising_2.yaml" + } + }, + "blimp_transitive": { + "task": "blimp_transitive", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "transitive", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/transitive.yaml" + } + }, + "blimp_wh_island": { + "task": "blimp_wh_island", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_island", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_island.yaml" + } + }, + "blimp_wh_questions_object_gap": { + "task": "blimp_wh_questions_object_gap", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_questions_object_gap", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_questions_object_gap.yaml" + } + }, + "blimp_wh_questions_subject_gap": { + "task": "blimp_wh_questions_subject_gap", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_questions_subject_gap", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_questions_subject_gap.yaml" + } + }, + "blimp_wh_questions_subject_gap_long_distance": { + "task": "blimp_wh_questions_subject_gap_long_distance", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_questions_subject_gap_long_distance", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_questions_subject_gap_long_distance.yaml" + } + }, + "blimp_wh_vs_that_no_gap": { + "task": "blimp_wh_vs_that_no_gap", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_vs_that_no_gap", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_vs_that_no_gap.yaml" + } + }, + "blimp_wh_vs_that_no_gap_long_distance": { + "task": "blimp_wh_vs_that_no_gap_long_distance", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_vs_that_no_gap_long_distance", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_vs_that_no_gap_long_distance.yaml" + } + }, + "blimp_wh_vs_that_with_gap": { + "task": "blimp_wh_vs_that_with_gap", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_vs_that_with_gap", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_vs_that_with_gap.yaml" + } + }, + "blimp_wh_vs_that_with_gap_long_distance": { + "task": "blimp_wh_vs_that_with_gap_long_distance", + "dataset_path": "nyu-mll/blimp", + "dataset_name": "wh_vs_that_with_gap_long_distance", + "validation_split": "train", + "doc_to_text": "", + "doc_to_target": 0, + "unsafe_code": false, + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": "{{[sentence_good, sentence_bad]}}", + "doc_to_target": 0, + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/blimp/wh_vs_that_with_gap_long_distance.yaml" + } + }, + "boolq": { + "task": "boolq", + "dataset_path": "aps/super_glue", + "dataset_name": "boolq", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "{{passage}}\nQuestion: {{question}}?\nAnswer:", + "doc_to_target": "label", + "unsafe_code": false, + "doc_to_choice": [ + "no", + "yes" + ], + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "{{passage}}\nQuestion: {{question}}?\nAnswer:", + "doc_to_choice": [ + "no", + "yes" + ], + "doc_to_target": "label", + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "passage", + "metadata": { + "version": 2.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/super_glue/boolq/default.yaml" + } + }, + "hellaswag": { + "task": "hellaswag", + "dataset_path": "Rowan/hellaswag", + "training_split": "train", + "validation_split": "validation", + "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n def _process_doc(doc):\n ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n out_doc = {\n \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n \"gold\": int(doc[\"label\"]),\n }\n return out_doc\n\n return dataset.map(_process_doc)\n", + "doc_to_text": "{{query}}", + "doc_to_target": "{{label}}", + "unsafe_code": false, + "doc_to_choice": "choices", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": "", + "fewshot_indices": null, + "samples": null, + "doc_to_text": "{{query}}", + "doc_to_choice": "choices", + "doc_to_target": "{{label}}", + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/hellaswag/hellaswag.yaml" + } + }, + "piqa": { + "task": "piqa", + "dataset_path": "baber/piqa", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "Question: {{goal}}\nAnswer:", + "doc_to_target": "label", + "unsafe_code": false, + "doc_to_choice": "{{[sol1, sol2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "Question: {{goal}}\nAnswer:", + "doc_to_choice": "{{[sol1, sol2]}}", + "doc_to_target": "label", + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "goal", + "metadata": { + "version": 1.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/piqa/piqa.yaml" + } + }, + "wikitext": { + "task": "wikitext", + "dataset_path": "EleutherAI/wikitext_document_level", + "dataset_name": "wikitext-2-raw-v1", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n", + "unsafe_code": false, + "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + "split": null, + "process_docs": null, + "fewshot_indices": null, + "samples": null, + "doc_to_text": "", + "doc_to_choice": null, + "doc_to_target": "", + "gen_prefix": null, + "fewshot_delimiter": "\n\n", + "target_delimiter": " " + }, + "num_fewshot": 0, + "metric_list": [ + { + "metric": "word_perplexity" + }, + { + "metric": "byte_perplexity" + }, + { + "metric": "bits_per_byte" + } + ], + "output_type": "loglikelihood_rolling", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{page}}", + "metadata": { + "version": 2.0, + "pretrained": "/home/nvidia/pretrain/michel-micro/checkpoint-80000/", + "dtype": "float", + "config_source": "/home/nvidia/lm-evaluation-harness/lm_eval/tasks/wikitext/wikitext.yaml" + } + }, + "winogrande": { + "task": "winogrande", + "dataset_path": "allenai/winogrande", + "dataset_name": "winogrande_xl", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "unsafe_code": false, + "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "default", + 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32-bit, 64-bit\nAddress sizes: 46 bits physical, 48 bits virtual\nByte Order: Little Endian\nCPU(s): 36\nOn-line CPU(s) list: 0-35\nVendor ID: GenuineIntel\nModel name: Intel(R) Xeon(R) CPU E5-2695 v4 @ 2.10GHz\nCPU family: 6\nModel: 79\nThread(s) per core: 2\nCore(s) per socket: 18\nSocket(s): 1\nStepping: 1\nCPU(s) scaling MHz: 45%\nCPU max MHz: 3300,0000\nCPU min MHz: 1200,0000\nBogoMIPS: 4190,53\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 pti intel_ppin ssbd ibrs ibpb stibp tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms 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Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT vulnerable\n\nVersions of relevant libraries:\n[pip3] numpy==2.4.6\n[pip3] nvidia-cublas==13.1.1.3\n[pip3] nvidia-cuda-cupti==13.0.85\n[pip3] nvidia-cuda-nvrtc==13.0.88\n[pip3] nvidia-cuda-runtime==13.0.96\n[pip3] nvidia-cudnn-cu13==9.20.0.48\n[pip3] nvidia-cufft==12.0.0.61\n[pip3] nvidia-curand==10.4.0.35\n[pip3] nvidia-cusolver==12.0.4.66\n[pip3] nvidia-cusparse==12.6.3.3\n[pip3] nvidia-cusparselt-cu13==0.8.1\n[pip3] nvidia-nccl-cu13==2.29.7\n[pip3] nvidia-nvjitlink==13.0.88\n[pip3] nvidia-nvtx==13.0.85\n[pip3] torch==2.12.0\n[pip3] triton==3.7.0\n[conda] Could not collect", + "transformers_version": "5.10.2", + "lm_eval_version": "0.4.13.dev0", + "upper_git_hash": 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