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Eagle-7B-1T-ac/results.json ADDED
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+ {
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+ "results": {
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+ "arc_challenge": {
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+ "acc,none": 0.42918088737201365,
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+ "acc_stderr,none": 0.014464085894870677,
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+ "acc_norm,none": 0.4761092150170648,
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+ "acc_norm_stderr,none": 0.014594701798071666,
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+ "alias": "arc_challenge"
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+ }
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+ },
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+ "configs": {
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+ "arc_challenge": {
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+ "task": "arc_challenge",
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+ "group": [
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+ "ai2_arc"
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+ ],
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+ "dataset_path": "allenai/ai2_arc",
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+ "dataset_name": "ARC-Challenge",
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+ "training_split": "train",
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+ "validation_split": "validation",
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+ "test_split": "test",
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+ "doc_to_text": "Question: {{question}}\nAnswer:",
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+ "doc_to_target": "{{choices.label.index(answerKey)}}",
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+ "doc_to_choice": "{{choices.text}}",
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+ "description": "",
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+ "target_delimiter": " ",
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+ "fewshot_delimiter": "\n\n",
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+ "num_fewshot": 25,
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+ "metric_list": [
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+ {
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+ "metric": "acc",
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+ "aggregation": "mean",
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+ "higher_is_better": true
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+ },
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+ {
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+ "metric": "acc_norm",
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+ "aggregation": "mean",
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+ "higher_is_better": true
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+ }
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+ ],
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+ "output_type": "multiple_choice",
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+ "repeats": 1,
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+ "should_decontaminate": true,
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+ "doc_to_decontamination_query": "Question: {{question}}\nAnswer:",
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+ "metadata": {
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+ "version": 1.0
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+ }
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+ }
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+ },
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+ "versions": {
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+ "arc_challenge": 1.0
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+ },
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+ "n-shot": {
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+ "arc_challenge": 25
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+ },
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+ "config": {
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+ "model": "hf",
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+ "model_args": "pretrained=RWKV/rwkv-5-world-7b,dtype=float16,trust_remote_code=True",
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+ "batch_size": "auto",
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+ "batch_sizes": [
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+ 8
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+ ],
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+ "device": null,
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+ "use_cache": null,
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+ "limit": null,
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+ "bootstrap_iters": 100000,
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+ "gen_kwargs": null
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+ },
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+ "git_hash": "1554066c"
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+ }
Eagle-7B-1T-hs/results.json ADDED
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+ {
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+ "results": {
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+ "hellaswag": {
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+ "acc,none": 0.5274845648277235,
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+ "acc_stderr,none": 0.00498223713340941,
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+ "acc_norm,none": 0.7165903206532563,
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+ "acc_norm_stderr,none": 0.004497325533959324,
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+ "alias": "hellaswag"
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+ }
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+ },
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+ "configs": {
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+ "hellaswag": {
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+ "task": "hellaswag",
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+ "group": [
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+ "multiple_choice"
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+ ],
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+ "dataset_path": "hellaswag",
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+ "training_split": "train",
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+ "validation_split": "validation",
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+ "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",
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+ "doc_to_text": "{{query}}",
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+ "doc_to_target": "{{label}}",
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+ "doc_to_choice": "choices",
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+ "description": "",
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+ "target_delimiter": " ",
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+ "fewshot_delimiter": "\n\n",
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+ "num_fewshot": 10,
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+ "metric_list": [
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+ {
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+ "metric": "acc",
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+ "aggregation": "mean",
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+ "higher_is_better": true
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+ },
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+ {
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+ "metric": "acc_norm",
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+ "aggregation": "mean",
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+ "higher_is_better": true
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+ }
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+ ],
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+ "output_type": "multiple_choice",
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+ "repeats": 1,
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+ "should_decontaminate": false,
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+ "metadata": {
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+ "version": 1.0
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+ }
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+ }
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+ },
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+ "versions": {
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+ "hellaswag": 1.0
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+ },
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+ "n-shot": {
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+ "hellaswag": 10
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+ },
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+ "config": {
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+ "model": "hf",
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+ "model_args": "pretrained=RWKV/rwkv-5-world-7b,dtype=float16,trust_remote_code=True",
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+ "batch_size": "auto",
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+ "batch_sizes": [
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+ 8
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+ ],
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+ "device": null,
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+ "use_cache": null,
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+ "limit": null,
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+ "bootstrap_iters": 100000,
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+ "gen_kwargs": null
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+ },
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+ "git_hash": "1554066c"
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+ }