Adding samples results for hellaswag_id to google/gemma-2-2b

.gitattributes

@@ -57,3 +57,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+google__gemma-2-2b/samples_hellaswag_id_2024-12-03T18-18-36.739078.jsonl filter=lfs diff=lfs merge=lfs -text

google__gemma-2-2b/results_2024-12-03T18-18-36.739078.json

@@ -0,0 +1,123 @@
+{
+  "results": {
+    "hellaswag_id": {
+      "alias": "hellaswag_id",
+      "acc,none": 0.4150191061638146,
+      "acc_stderr,none": 0.006351536446779069,
+      "acc_norm,none": 0.5592291078252202,
+      "acc_norm_stderr,none": 0.006399930323054428
+    }
+  },
+  "group_subtasks": {
+    "hellaswag_id": []
+  },
+  "configs": {
+    "hellaswag_id": {
+      "task": "hellaswag_id",
+      "tag": [
+        "hellaswag_multilingual"
+      ],
+      "dataset_path": "richmondsin/m_hellaswag",
+      "dataset_name": "id",
+      "validation_split": "val",
+      "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.lstrip()}}",
+      "doc_to_choice": "choices",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 10,
+      "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
+      }
+    }
+  },
+  "versions": {
+    "hellaswag_id": 1.0
+  },
+  "n-shot": {
+    "hellaswag_id": 10
+  },
+  "higher_is_better": {
+    "hellaswag_id": {
+      "acc": true,
+      "acc_norm": true
+    }
+  },
+  "n-samples": {
+    "hellaswag_id": {
+      "original": 6019,
+      "effective": 6019
+    }
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=google/gemma-2-2b",
+    "model_num_parameters": 2614341888,
+    "model_dtype": "torch.float32",
+    "model_revision": "main",
+    "model_sha": "c5ebcd40d208330abc697524c919956e692655cf",
+    "batch_size": "auto",
+    "batch_sizes": [
+      1
+    ],
+    "device": "cuda:0",
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null,
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "361fccb",
+  "date": 1733244303.2900927,
+  "pretty_env_info": "PyTorch version: 2.5.0+cu124\nIs debug build: False\nCUDA used to build PyTorch: 12.4\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 20.04 LTS (x86_64)\nGCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0\nClang version: Could not collect\nCMake version: version 3.16.3\nLibc version: glibc-2.31\n\nPython version: 3.12.4 | packaged by Anaconda, Inc. | (main, Jun 18 2024, 15:12:24) [GCC 11.2.0] (64-bit runtime)\nPython platform: Linux-5.15.0-46-generic-x86_64-with-glibc2.31\nIs CUDA available: True\nCUDA runtime version: Could not collect\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA RTX A4000\nGPU 1: NVIDIA RTX A4000\nGPU 2: NVIDIA RTX A4000\nGPU 3: NVIDIA RTX A4000\n\nNvidia driver version: 560.35.03\ncuDNN version: Probably one of the following:\n/usr/lib/x86_64-linux-gnu/libcudnn.so.8.5.0\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.5.0\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.5.0\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.5.0\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.5.0\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.5.0\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.5.0\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                    x86_64\nCPU op-mode(s):                  32-bit, 64-bit\nByte Order:                      Little Endian\nAddress sizes:                   46 bits physical, 48 bits virtual\nCPU(s):                          24\nOn-line CPU(s) list:             0-23\nThread(s) per core:              2\nCore(s) per socket:              12\nSocket(s):                       1\nNUMA node(s):                    1\nVendor ID:                       GenuineIntel\nCPU family:                      6\nModel:                           85\nModel name:                      Intel(R) Core(TM) i9-10920X CPU @ 3.50GHz\nStepping:                        7\nCPU MHz:                         4372.093\nCPU max MHz:                     4800.0000\nCPU min MHz:                     1200.0000\nBogoMIPS:                        6999.82\nVirtualization:                  VT-x\nL1d cache:                       384 KiB\nL1i cache:                       384 KiB\nL2 cache:                        12 MiB\nL3 cache:                        19.3 MiB\nNUMA node0 CPU(s):               0-23\nVulnerability Itlb multihit:     KVM: Mitigation: VMX disabled\nVulnerability L1tf:              Not affected\nVulnerability Mds:               Not affected\nVulnerability Meltdown:          Not affected\nVulnerability Mmio stale data:   Mitigation; Clear CPU buffers; SMT vulnerable\nVulnerability Retbleed:          Mitigation; Enhanced IBRS\nVulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:        Mitigation; Enhanced IBRS, IBPB conditional, RSB filling\nVulnerability Srbds:             Not affected\nVulnerability Tsx async abort:   Mitigation; TSX disabled\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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx 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 invpcid_single ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512_vnni md_clear flush_l1d arch_capabilities\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] torch==2.5.0\n[pip3] torchaudio==2.5.0\n[pip3] torchvision==0.20.0\n[pip3] triton==3.1.0\n[conda] blas                      1.0                         mkl  \n[conda] mkl                       2021.4.0           h06a4308_640  \n[conda] mkl-service               2.4.0           py310h7f8727e_0  \n[conda] mkl_fft                   1.3.1           py310hd6ae3a3_0  \n[conda] mkl_random                1.2.2           py310h00e6091_0  \n[conda] numpy                     1.23.5          py310hd5efca6_0  \n[conda] numpy-base                1.23.5          py310h8e6c178_0  \n[conda] numpydoc                  1.5.0           py310h06a4308_0  \n[conda] pytorch                   1.12.1          cpu_py310hb1f1ab4_1  ",
+  "transformers_version": "4.46.0",
+  "upper_git_hash": "361fccbbd4e9842fa72c3b6c7d7c082a50c07504",
+  "tokenizer_pad_token": [
+    "<pad>",
+    "0"
+  ],
+  "tokenizer_eos_token": [
+    "<eos>",
+    "1"
+  ],
+  "tokenizer_bos_token": [
+    "<bos>",
+    "2"
+  ],
+  "eot_token_id": 1,
+  "max_length": 8192,
+  "task_hashes": {
+    "hellaswag_id": "8b34e41f86d06bdbc4855bf0fb03ec280f5a31b522f2a67e73ca6168487014f0"
+  },
+  "model_source": "hf",
+  "model_name": "google/gemma-2-2b",
+  "model_name_sanitized": "google__gemma-2-2b",
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "fewshot_as_multiturn": false,
+  "chat_template": null,
+  "chat_template_sha": null,
+  "start_time": 8081946.206054469,
+  "end_time": 8105564.482046235,
+  "total_evaluation_time_seconds": "23618.275991766714"
+}

google__gemma-2-2b/samples_hellaswag_id_2024-12-03T18-18-36.739078.jsonl

@@ -0,0 +1,3 @@
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