he-cantillation

This model is a fine-tuned version of cantillation/Teamim-large-v2_Random-True_OldData_date-07-06-2024_16-07-57 on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0899
• eval_wer: 9.8928
• eval_avg_precision_Exact: 0.9232
• eval_avg_recall_Exact: 0.9228
• eval_avg_f1_Exact: 0.9227
• eval_avg_precision_Letter_Shift: 0.9383
• eval_avg_recall_Letter_Shift: 0.9381
• eval_avg_f1_Letter_Shift: 0.9379
• eval_avg_precision_Word_Level: 0.9405
• eval_avg_recall_Word_Level: 0.9404
• eval_avg_f1_Word_Level: 0.9401
• eval_avg_precision_Word_Shift: 0.9772
• eval_avg_recall_Word_Shift: 0.9777
• eval_avg_f1_Word_Shift: 0.9771
• eval_precision_median_exact: 1.0
• eval_recall_median_exact: 1.0
• eval_f1_median_exact: 1.0
• eval_precision_max_exact: 1.0
• eval_recall_max_exact: 1.0
• eval_f1_max_exact: 1.0
• eval_precision_min_Exact: 0.0
• eval_recall_min_Exact: 0.0
• eval_f1_min_Exact: 0.0
• eval_precision_min_Letter_Shift: 0.0
• eval_recall_min_Letter_Shift: 0.0
• eval_f1_min_Letter_Shift: 0.0
• eval_precision_min_Word_Level: 0.0
• eval_recall_min_Word_Level: 0.0
• eval_f1_min_Word_Level: 0.0
• eval_precision_min_Word_Shift: 0.1429
• eval_recall_min_Word_Shift: 0.1
• eval_f1_min_Word_Shift: 0.1176
• eval_runtime: 2336.8917
• eval_samples_per_second: 1.152
• eval_steps_per_second: 0.036
• epoch: 0.56
• step: 7000

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 8000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.42.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.16.1
• Tokenizers 0.19.1