SentenceTransformer based on cl-nagoya/sup-simcse-ja-base

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: cl-nagoya/sup-simcse-ja-base
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 768 dimensions
• Similarity Function: Cosine Similarity

Model Sources

• Documentation: Sentence Transformers Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)

Usage

Direct Usage (Sentence Transformers)

Training Details

Training Dataset

Unnamed Dataset

• Size: 72 training samples
• Columns: sentence and label
• Approximate statistics based on the first 72 samples:

  	sentence	label
  type	string	int
  details	min: 11 tokens mean: 16.21 tokens max: 27 tokens	0: ~0.50% 1: ~0.50% 2: ~0.50% 3: ~0.50% 4: ~0.50% 5: ~0.50% 6: ~0.50% 7: ~0.50% 8: ~0.50% 9: ~0.50% 10: ~0.50% 11: ~0.50% 12: ~0.50% 13: ~0.50% 14: ~0.50% 15: ~0.50% 16: ~0.50% 17: ~0.50% 18: ~0.50% 19: ~0.50% 20: ~0.50% 21: ~0.50% 22: ~0.50% 23: ~0.50% 24: ~0.50% 25: ~0.50% 26: ~0.50% 27: ~0.50% 28: ~0.50% 29: ~0.50% 30: ~0.50% 31: ~0.50% 32: ~0.50% 33: ~0.50% 34: ~0.50% 35: ~0.50% 36: ~0.50% 37: ~0.50% 38: ~0.50% 39: ~0.50% 40: ~0.50% 41: ~0.50% 42: ~0.50% 43: ~0.50% 44: ~0.60% 45: ~0.70% 46: ~0.50% 47: ~0.50% 48: ~0.50% 49: ~0.50% 50: ~0.50% 51: ~0.50% 52: ~0.50% 53: ~0.50% 54: ~0.50% 55: ~0.50% 56: ~0.50% 57: ~0.80% 58: ~0.50% 59: ~0.50% 60: ~0.50% 61: ~0.50% 62: ~0.50% 63: ~0.50% 64: ~0.50% 65: ~0.50% 66: ~0.50% 67: ~0.50% 68: ~0.50% 69: ~0.50% 70: ~0.50% 71: ~0.50% 72: ~0.50% 73: ~0.50% 74: ~0.50% 75: ~0.50% 76: ~0.50% 77: ~0.50% 78: ~0.50% 79: ~0.50% 80: ~0.50% 81: ~0.50% 82: ~0.50% 83: ~0.50% 84: ~0.50% 85: ~0.50% 86: ~0.50% 87: ~0.50% 88: ~0.60% 89: ~0.50% 90: ~0.50% 91: ~0.50% 92: ~0.50% 93: ~0.50% 94: ~0.50% 95: ~1.20% 96: ~1.70% 97: ~3.90% 98: ~0.50% 99: ~0.50% 100: ~0.50% 101: ~0.60% 102: ~0.50% 103: ~0.50% 104: ~0.50% 105: ~0.50% 106: ~0.50% 107: ~1.20% 108: ~0.50% 109: ~0.50% 110: ~0.50% 111: ~0.50% 112: ~0.50% 113: ~0.50% 114: ~0.50% 115: ~0.50% 116: ~0.50% 117: ~0.50% 118: ~0.50% 119: ~0.50% 120: ~0.50% 121: ~0.50% 122: ~0.50% 123: ~0.50% 124: ~0.50% 125: ~0.50% 126: ~0.50% 127: ~0.50% 128: ~0.50% 129: ~0.50% 130: ~0.50% 131: ~0.50% 132: ~0.50% 133: ~0.50% 134: ~0.50% 135: ~0.50% 136: ~0.50% 137: ~0.50% 138: ~0.50% 139: ~0.50% 140: ~0.50% 141: ~0.50% 142: ~0.50% 143: ~0.50% 144: ~0.50% 145: ~0.50% 146: ~0.70% 147: ~0.50% 148: ~3.10% 149: ~0.50% 150: ~2.30% 151: ~0.50% 152: ~0.50% 153: ~0.50% 154: ~0.50% 155: ~0.50% 156: ~0.50% 157: ~0.50% 158: ~0.50% 159: ~0.50% 160: ~0.50% 161: ~0.50% 162: ~0.50% 163: ~0.50% 164: ~0.50% 165: ~0.50% 166: ~0.50% 167: ~0.50% 168: ~0.50% 169: ~0.50% 170: ~0.50% 171: ~0.50% 172: ~0.50% 173: ~0.50% 174: ~0.50% 175: ~0.50% 176: ~0.50% 177: ~0.10%

• Samples:

  sentence	label
  科目：コンクリート。名称：免震基礎天端ｸﾞﾗｳﾄ注入。	0
  科目：コンクリート。名称：免震基礎天端ｸﾞﾗｳﾄ注入。	0
  科目：コンクリート。名称：免震基礎天端ｸﾞﾗｳﾄ注入。	0

• Loss: BatchAllTripletLoss

Training Hyperparameters

Non-Default Hyperparameters

• per_device_train_batch_size: 512
• per_device_eval_batch_size: 512
• learning_rate: 1e-05
• weight_decay: 0.01
• num_train_epochs: 250
• warmup_ratio: 0.1
• fp16: True
• batch_sampler: group_by_label

All Hyperparameters

Training Logs

Framework Versions

• Python: 3.11.11
• Sentence Transformers: 3.4.1
• Transformers: 4.50.2
• PyTorch: 2.6.0+cu124
• Accelerate: 1.5.2
• Datasets: 3.5.0
• Tokenizers: 0.21.1

Citation

BibTeX

Sentence Transformers

BatchAllTripletLoss