bert-large-cantonese-sts
This model is a fine-tuned version of hon9kon9ize/bert-large-cantonese on the hon9kon9ize/yue-sts dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
Training results
Framework versions
- Transformers 4.43.3
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1
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Model tree for hon9kon9ize/bert-large-cantonese-sts
Base model
hon9kon9ize/bert-large-cantoneseSpace using hon9kon9ize/bert-large-cantonese-sts 1
Evaluation results
- pearson_cosine on sts devself-reported0.820
- spearman_cosine on sts devself-reported0.811
- pearson_manhattan on sts devself-reported0.823
- spearman_manhattan on sts devself-reported0.811
- pearson_euclidean on sts devself-reported0.822
- spearman_euclidean on sts devself-reported0.811
- pearson_dot on sts devself-reported0.820
- spearman_dot on sts devself-reported0.811