| {"eval_library":{"additional_details":{"dataset":"fquad","few_shot":"true","languages":"[\"fr\"]","litellm_version":null,"raw_results":"[{\"f1\": 75.04300933622719, \"em\": 47.34848484848485}, {\"f1\": 74.49130844355544, \"em\": 46.39878695981805}, {\"f1\": 76.1598536444198, \"em\": 48.873348873348874}, {\"f1\": 75.26560602783863, \"em\": 47.1841704718417}, {\"f1\": 71.89097995042816, \"em\": 45.720894371626834}, {\"f1\": 76.05126549095377, \"em\": 48.54961832061068}, {\"f1\": 74.3564038673692, \"em\": 47.50390015600624}, {\"f1\": 73.24357239384071, \"em\": 46.38364779874214}, {\"f1\": 74.35521606122208, \"em\": 49.14860681114551}, {\"f1\": 74.54822522693647, \"em\": 46.06481481481482}]","task":"reading-comprehension","torch_version":"2.7.0","transformers_version":"4.52.4","validation_split":"false","vllm_version":"0.9.1","xgrammar_version":"0.2.0"},"name":"euroeval","version":"15.10.0.dev0"},"evaluation_id":"fquad/CohereForAI/aya-23-35B/1781766557","evaluation_results":[{"evaluation_name":"test_f1","metric_config":{"lower_is_better":false,"max_score":100,"min_score":0,"score_type":"continuous"},"score_details":{"details":{"num_failed_instances":"0.0"},"score":74.54054404427914,"uncertainty":{"confidence_interval":{"confidence_level":0.95,"lower":73.75502945596902,"method":"bootstrap","upper":75.32605863258927},"num_samples":10}},"source_data":{"dataset_name":"fquad","source_type":"hf_dataset"}},{"evaluation_name":"test_em","metric_config":{"lower_is_better":false,"max_score":100,"min_score":0,"score_type":"continuous"},"score_details":{"details":{"num_failed_instances":"0.0"},"score":47.31762734264397,"uncertainty":{"confidence_interval":{"confidence_level":0.95,"lower":46.56758194136147,"method":"bootstrap","upper":48.06767274392648},"num_samples":10}},"source_data":{"dataset_name":"fquad","source_type":"hf_dataset"}}],"evaluation_timestamp":"2026-06-18T07:09:17.004473+00:00","model_info":{"additional_details":{"commercially_licensed":false,"generative":"true","generative_type":"instruction_tuned","max_sequence_length":"8192","merge":"false","model_url":"https://hf.co/CohereForAI/aya-23-35B","num_model_parameters":"34980831232","open":true,"release_date":"2024-05-23","trained_from_scratch":false,"vocabulary_size":"256000"},"id":"CohereForAI/aya-23-35B","inference_engine":{"name":"vllm","version":"0.9.1"},"name":"CohereForAI/aya-23-35B"},"retrieved_timestamp":"1781766557","schema_version":"0.2.1","source_metadata":{"evaluator_relationship":"third_party","source_name":"EuroEval","source_organization_name":"EuroEval","source_organization_url":"https://euroeval.com","source_type":"evaluation_run"}} | |
Xet Storage Details
- Size:
- 2.64 kB
- Xet hash:
- 891489b95974c9ff177d7b4f70c9be9bf8999c4f82ea223f722f59c2095ec08b
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.