wav2vec2-large-300m-colab-only-gn

karanthgreeshma/wav2vec2-large-300m-colab-only-gn

wav2vec2-large-300m-colab-only-gn is a automatic speech recognition model from karanthgreeshma. 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: wav2vec2
Access: Public
Created: Oct 31, 2023
Updated: Nov 1, 2023
SHA: 877248c9

Base models

facebook/wav2vec2-xls-r-300m

Datasets

common_voice_13_0

Model card

From the Hugging Face model README

wav2vec2-large-300m-colab-only-gn

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5274
Wer: 0.5229

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
20.8148	0.45	25	13.5976	1.0
7.0188	0.9	50	5.5263	1.0
4.1285	1.35	75	3.6078	1.0
3.338	1.8	100	3.3217	1.0
3.2829	2.25	125	3.2781	1.0
3.272	2.7	150	3.2601	1.0
3.2224	3.15	175	3.2234	1.0
3.1949	3.6	200	3.1998	1.0
3.1846	4.05	225	3.1841	1.0
3.1615	4.5	250	3.1719	1.0
3.1367	4.95	275	3.1132	1.0
3.0111	5.41	300	2.9344	1.0
2.7786	5.86	325	2.5643	1.0
2.2106	6.31	350	1.8132	1.0
1.6365	6.76	375	1.4008	0.9982
1.178	7.21	400	1.0678	0.9845
0.8903	7.66	425	0.8744	0.9369
0.7429	8.11	450	0.7213	0.8752
0.5931	8.56	475	0.6681	0.8189
0.5592	9.01	500	0.6622	0.7895
0.4316	9.46	525	0.6177	0.7644
0.4098	9.91	550	0.5599	0.7874
0.3176	10.36	575	0.5649	0.7001
0.3142	10.81	600	0.5828	0.6867
0.3227	11.26	625	0.5505	0.6736
0.275	11.71	650	0.5432	0.6540
0.2783	12.16	675	0.5372	0.6462
0.2316	12.61	700	0.5078	0.6379
0.2281	13.06	725	0.5059	0.6161
0.2191	13.51	750	0.5175	0.5956
0.1911	13.96	775	0.5216	0.5929
0.1731	14.41	800	0.5069	0.5789
0.1743	14.86	825	0.5207	0.5971
0.1755	15.32	850	0.5436	0.6307
0.1568	15.77	875	0.5374	0.6001
0.1629	16.22	900	0.5429	0.6102
0.1418	16.67	925	0.5089	0.5762
0.136	17.12	950	0.5291	0.5878
0.1354	17.57	975	0.5381	0.5840
0.1351	18.02	1000	0.5511	0.5947
0.1252	18.47	1025	0.5204	0.5643
0.1215	18.92	1050	0.5385	0.5613
0.1188	19.37	1075	0.5063	0.5718
0.1209	19.82	1100	0.5211	0.5488
0.1091	20.27	1125	0.5245	0.5557
0.112	20.72	1150	0.4910	0.5587
0.102	21.17	1175	0.5192	0.5581
0.0947	21.62	1200	0.5500	0.5718
0.1066	22.07	1225	0.5288	0.5488
0.1011	22.52	1250	0.5180	0.5438
0.0974	22.97	1275	0.5089	0.5277
0.0926	23.42	1300	0.5222	0.5301
0.0871	23.87	1325	0.5135	0.5366
0.0808	24.32	1350	0.4990	0.5331
0.0739	24.77	1375	0.5281	0.5351
0.0841	25.23	1400	0.5321	0.5360
0.0743	25.68	1425	0.5508	0.5447
0.0809	26.13	1450	0.5228	0.5396
0.0631	26.58	1475	0.5284	0.5351
0.0788	27.03	1500	0.5250	0.5289
0.0754	27.48	1525	0.5204	0.5259
0.0663	27.93	1550	0.5275	0.5313
0.0645	28.38	1575	0.5288	0.5259
0.0729	28.83	1600	0.5268	0.5259
0.0656	29.28	1625	0.5277	0.5232
0.0703	29.73	1650	0.5274	0.5229

Framework versions

Transformers 4.34.1
Pytorch 2.0.1+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Oct 31, 2023
Updated: Nov 1, 2023