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
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