whisper-small-multilingual-spoken-ner-pipeline-lora

qmeeus/whisper-small-multilingual-spoken-ner-pipeline-lora

whisper-small-multilingual-spoken-ner-pipeline-lora is a machine learning model from qmeeus. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.

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

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At a glance

Library: peft
Model type: whisper_for_slu
Access: Public
Created: Jan 9, 2024
Updated: Jan 9, 2024
SHA: e508ee7d

Base models

qmeeus/whisper-small-multilingual-spoken-ner-pipeline-step-1

Datasets

facebook/voxpopuli

Model card

From the Hugging Face model README

WhisperForSpokenNER

This model is a fine-tuned version of /esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner on the facebook/voxpopuli de+es+fr+nl dataset. It achieves the following results on the evaluation set:

Loss: 0.2264
F1 Score: 0.6872
Label F1: 0.8325
Wer: 0.0980

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Score	Label F1	Wer
0.2746	0.36	200	0.2602	0.6565	0.8343	0.1090
0.2481	0.71	400	0.2465	0.6578	0.8348	0.1022
0.2385	1.07	600	0.2410	0.6685	0.8323	0.1048
0.2316	1.43	800	0.2374	0.6724	0.8317	0.1022
0.2291	1.79	1000	0.2348	0.6698	0.8292	0.0968
0.2205	2.14	1200	0.2334	0.6745	0.8339	0.0964
0.2211	2.5	1400	0.2319	0.6729	0.8327	0.0961
0.2163	2.86	1600	0.2305	0.6732	0.8300	0.0981
0.2108	3.22	1800	0.2299	0.6734	0.8328	0.0954
0.2104	3.57	2000	0.2297	0.6792	0.8369	0.0992
0.2124	3.93	2200	0.2279	0.6782	0.8346	0.0945
0.2027	4.29	2400	0.2279	0.6790	0.8336	0.0944
0.2055	4.65	2600	0.2275	0.6832	0.8347	0.0949
0.209	5.0	2800	0.2269	0.6822	0.8336	0.0983
0.2017	5.36	3000	0.2272	0.6835	0.8346	0.0979
0.2029	5.72	3200	0.2266	0.6819	0.8321	0.0966
0.201	6.08	3400	0.2266	0.6800	0.8327	0.0978
0.1985	6.43	3600	0.2267	0.6856	0.8335	0.0995
0.1996	6.79	3800	0.2265	0.6864	0.8343	0.0988
0.197	7.15	4000	0.2264	0.6843	0.8347	0.0986
0.1985	7.51	4200	0.2264	0.6838	0.8352	0.0985
0.1999	7.86	4400	0.2263	0.6861	0.8346	0.0978
0.1963	8.22	4600	0.2264	0.6864	0.8318	0.0978
0.1977	8.58	4800	0.2264	0.6875	0.8329	0.0979
0.1961	8.94	5000	0.2264	0.6872	0.8325	0.0980

Framework versions

PEFT 0.7.1.dev0
Transformers 4.37.0.dev0
Pytorch 2.1.0
Datasets 2.14.6
Tokenizers 0.14.1

Library: peft
Type: whisper_for_slu
Created: Jan 9, 2024
Updated: Jan 9, 2024