metadata

language: en
license: apache-2.0
tags:
  - automatic-speech-recognition
  - timit_asr
  - generated_from_trainer
datasets:
  - timit_asr
model-index:
  - name: sew-d-small-100k-timit
    results: []

sew-d-small-100k-timit

This model is a fine-tuned version of asapp/sew-d-small-100k on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

Loss: 1.7541
Wer: 0.8061

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: 32
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.2068	0.69	100	4.0802	1.0
2.9805	1.38	200	2.9792	1.0
2.9781	2.07	300	2.9408	1.0
2.9655	2.76	400	2.9143	1.0
2.8953	3.45	500	2.8775	1.0
2.7718	4.14	600	2.7787	1.0
2.6711	4.83	700	2.6401	0.9786
2.6403	5.52	800	2.5435	1.0392
2.4052	6.21	900	2.4580	1.0706
2.1708	6.9	1000	2.2800	1.0090
2.2555	7.59	1100	2.1493	0.9579
2.3673	8.28	1200	2.0709	0.9051
2.091	8.97	1300	2.0258	0.8926
1.8433	9.66	1400	1.9645	0.8243
1.6824	10.34	1500	1.9211	0.8707
2.2282	11.03	1600	1.8914	0.8695
1.9027	11.72	1700	1.8718	0.8343
1.6303	12.41	1800	1.8646	0.8232
1.648	13.1	1900	1.8297	0.8177
2.0429	13.79	2000	1.8127	0.8642
1.8833	14.48	2100	1.8005	0.8307
1.5996	15.17	2200	1.7926	0.8467
1.4876	15.86	2300	1.7795	0.8341
1.8925	16.55	2400	1.7716	0.8199
1.814	17.24	2500	1.7846	0.8086
1.536	17.93	2600	1.7655	0.8019
1.4476	18.62	2700	1.7599	0.8070
1.7629	19.31	2800	1.7589	0.8119
1.7646	20.0	2900	1.7541	0.8061

Framework versions

Transformers 4.12.0.dev0
Pytorch 1.8.1
Datasets 1.14.1.dev0
Tokenizers 0.10.3