wav2vec2-telugu_150

krishnateja/wav2vec2-telugu_150

wav2vec2-telugu_150 is a automatic speech recognition model from krishnateja. 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: Nov 11, 2022
Updated: Nov 13, 2022
SHA: a5971f21

Datasets

openslr

Spaces

Model card

From the Hugging Face model README

wav2vec2-telugu_150

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the openslr dataset.

It achieves the following results on the evaluation set:

Loss: 0.3312
Wer: 0.2213

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: 500
num_epochs: 150
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
6.096	3.84	400	0.5762	0.7029
0.427	7.69	800	0.3124	0.5148
0.208	11.54	1200	0.2994	0.4201
0.1506	15.38	1600	0.3106	0.3844
0.1223	19.23	2000	0.3080	0.3608
0.1094	23.08	2400	0.3206	0.3332
0.0949	26.92	2800	0.3085	0.3253
0.0802	30.77	3200	0.3076	0.3425
0.0713	34.61	3600	0.3280	0.3398
0.0687	38.46	4000	0.3042	0.3081
0.0613	42.31	4400	0.3227	0.3073
0.0548	46.15	4800	0.3152	0.3213
0.0508	50.0	5200	0.3259	0.3107
0.0455	53.84	5600	0.3046	0.2881
0.0427	57.69	6000	0.2779	0.3007
0.0391	61.54	6400	0.2996	0.2693
0.0388	65.38	6800	0.3016	0.2695
0.0339	69.23	7200	0.3225	0.2935
0.0312	73.08	7600	0.2907	0.2942
0.029	76.92	8000	0.3148	0.3029
0.0254	80.77	8400	0.3118	0.2996
0.0229	84.61	8800	0.3022	0.2993
0.0231	88.46	9200	0.3203	0.2465
0.019	92.31	9600	0.3223	0.2460
0.0173	96.15	10000	0.3178	0.2501
0.0168	100.0	10400	0.2937	0.2415
0.015	103.84	10800	0.3062	0.2415
0.014	107.69	11200	0.3104	0.2383
0.012	111.54	11600	0.3308	0.2408
0.0111	115.38	12000	0.3228	0.2335
0.01	119.23	12400	0.3228	0.2374
0.0096	123.08	12800	0.3241	0.2304
0.009	126.92	13200	0.3237	0.2295
0.0075	130.77	13600	0.3221	0.2261
0.0065	134.61	14000	0.3310	0.2277
0.0064	138.46	14400	0.3348	0.2266
0.0064	142.31	14800	0.3330	0.2229
0.0056	146.15	15200	0.3310	0.2229
0.0053	150.0	15600	0.3312	0.2213

Test results

WER(without LM): 42.8%

WER(with LM): 42%

Framework versions

Transformers 4.24.0
Pytorch 1.13.0+cu117
Datasets 2.6.1
Tokenizers 0.13.2

ps: 150 in repo name denotes number of epochs

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Nov 11, 2022
Updated: Nov 13, 2022