Teamim-large-v2_Random-True_date-06-06-2024_21-59-43

cantillation/Teamim-large-v2_Random-True_date-06-06-2024_21-59-43

Teamim-large-v2_Random-True_date-06-06-2024_21-59-43 is a automatic speech recognition model from cantillation. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: whisper
Access: Public
Created: Jun 6, 2024
Updated: Jun 7, 2024
SHA: bc301485

Base models

openai/whisper-large-v2

Model card

From the Hugging Face model README

he-cantillation

This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1029
Wer: 11.7332
Avg Precision Exact: 0.9091
Avg Recall Exact: 0.9078
Avg F1 Exact: 0.9081
Avg Precision Letter Shift: 0.9280
Avg Recall Letter Shift: 0.9269
Avg F1 Letter Shift: 0.9271
Avg Precision Word Level: 0.9303
Avg Recall Word Level: 0.9294
Avg F1 Word Level: 0.9295
Avg Precision Word Shift: 0.9756
Avg Recall Word Shift: 0.9759
Avg F1 Word Shift: 0.9754
Precision Median Exact: 1.0
Recall Median Exact: 1.0
F1 Median Exact: 1.0
Precision Max Exact: 1.0
Recall Max Exact: 1.0
F1 Max Exact: 1.0
Precision Min Exact: 0.0
Recall Min Exact: 0.0
F1 Min Exact: 0.0
Precision Min Letter Shift: 0.0
Recall Min Letter Shift: 0.0
F1 Min Letter Shift: 0.0
Precision Min Word Level: 0.0
Recall Min Word Level: 0.0
F1 Min Word Level: 0.0
Precision Min Word Shift: 0.1429
Recall Min Word Shift: 0.1
F1 Min Word Shift: 0.1176

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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Avg Precision Exact	Avg Recall Exact	Avg F1 Exact	Avg Precision Letter Shift	Avg Recall Letter Shift	Avg F1 Letter Shift	Avg Precision Word Level	Avg Recall Word Level	Avg F1 Word Level	Avg Precision Word Shift	Avg Recall Word Shift	Avg F1 Word Shift	Precision Median Exact	Recall Median Exact	F1 Median Exact	Precision Max Exact	Recall Max Exact	F1 Max Exact	Precision Min Exact	Recall Min Exact	F1 Min Exact	Precision Min Letter Shift	Recall Min Letter Shift	F1 Min Letter Shift	Precision Min Word Level	Recall Min Word Level	F1 Min Word Level	Precision Min Word Shift	Recall Min Word Shift	F1 Min Word Shift
No log	8e-05	1	5.7968	117.0732	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
0.1322	0.08	1000	0.1679	24.1907	0.8065	0.8169	0.8107	0.8367	0.8476	0.8410	0.8414	0.8525	0.8458	0.9193	0.9337	0.9252	0.8889	0.9	0.8889	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.0895	0.16	2000	0.1293	17.7679	0.8618	0.8637	0.8621	0.8863	0.8883	0.8867	0.8902	0.8927	0.8908	0.9500	0.9551	0.9518	0.9231	0.9231	0.9286	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1111	0.1111	0.125
0.0448	0.24	3000	0.1182	15.4065	0.8816	0.8881	0.8843	0.9059	0.9128	0.9088	0.9087	0.9156	0.9116	0.9607	0.9675	0.9635	0.9310	0.9375	0.9524	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1429	0.125	0.1333
0.0341	0.32	4000	0.1153	14.7894	0.8871	0.8897	0.8879	0.9110	0.9137	0.9118	0.9137	0.9170	0.9148	0.9646	0.9692	0.9663	0.9375	0.9444	0.9565	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1429	0.1111	0.125
0.022	0.4	5000	0.1076	13.5772	0.8993	0.8954	0.8969	0.9224	0.9185	0.9199	0.9251	0.9216	0.9229	0.9710	0.9696	0.9698	1.0	1.0	0.9630	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1429	0.0833	0.1053
0.0172	0.48	6000	0.1037	12.3245	0.9086	0.9078	0.9078	0.9283	0.9277	0.9276	0.9306	0.9302	0.9300	0.9727	0.9740	0.9729	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0769	0.0769	0.0769
0.0094	0.56	7000	0.1045	12.0806	0.9059	0.9058	0.9054	0.9257	0.9257	0.9253	0.9279	0.9280	0.9275	0.9733	0.9747	0.9735	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1429	0.1	0.1176
0.014	0.64	8000	0.1029	11.7332	0.9091	0.9078	0.9081	0.9280	0.9269	0.9271	0.9303	0.9294	0.9295	0.9756	0.9759	0.9754	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1429	0.1	0.1176

Framework versions

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

Task: Automatic Speech Recognition
Library: transformers
Type: whisper
License: apache-2.0
Languages: he
Created: Jun 6, 2024
Updated: Jun 7, 2024