timit-xls-r-300m

SpeechResearch/timit-xls-r-300m

timit-xls-r-300m is a automatic speech recognition model from SpeechResearch. 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: Apr 14, 2024
Updated: Apr 14, 2024
SHA: b44502a3

Base models

facebook/wav2vec2-xls-r-300m

Datasets

timit_asr

Model card

From the Hugging Face model README

timit-xls-r-300m

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

Loss: 0.4457
Wer: 0.2466

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.0049	1.72	500	1.9735	1.0655
1.033	3.45	1000	0.6172	0.5115
0.4499	5.17	1500	0.5231	0.4395
0.2551	6.9	2000	0.4768	0.3772
0.1724	8.62	2500	0.4699	0.3626
0.133	10.34	3000	0.4346	0.3329
0.1082	12.07	3500	0.4479	0.3163
0.0886	13.79	4000	0.4393	0.3167
0.0766	15.52	4500	0.4920	0.3100
0.0637	17.24	5000	0.4510	0.3013
0.0607	18.97	5500	0.4284	0.2808
0.0495	20.69	6000	0.4270	0.2820
0.0479	22.41	6500	0.4294	0.2852
0.0444	24.14	7000	0.4456	0.2816
0.0378	25.86	7500	0.4236	0.2763
0.0325	27.59	8000	0.4365	0.2849
0.031	29.31	8500	0.4482	0.2862
0.0285	31.03	9000	0.4388	0.2691
0.0252	32.76	9500	0.4253	0.2692
0.0229	34.48	10000	0.4598	0.2641
0.0223	36.21	10500	0.4462	0.2533
0.0188	37.93	11000	0.4350	0.2673
0.0163	39.66	11500	0.4460	0.2608
0.0167	41.38	12000	0.4441	0.2683
0.0138	43.1	12500	0.4290	0.2528
0.0127	44.83	13000	0.4360	0.2508
0.0124	46.55	13500	0.4406	0.2511
0.0107	48.28	14000	0.4482	0.2477
0.0108	50.0	14500	0.4457	0.2466

Framework versions

Transformers 4.39.3
Pytorch 2.0.1+cu117
Datasets 2.18.0
Tokenizers 0.15.2

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Apr 14, 2024
Updated: Apr 14, 2024