metadata

license: apache-2.0
tags:
  - automatic-speech-recognition
  - timit_asr
  - generated_from_trainer
datasets:
  - timit_asr
base_model: facebook/wav2vec2-base
model-index:
  - name: wav2vec2-base-timit-fine-tuned
    results: []

wav2vec2-base-timit-fine-tuned

This model is a fine-tuned version of facebook/wav2vec2-base on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

Loss: 0.3457
Wer: 0.2151

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
3.1621	0.69	100	3.1102	1.0
2.9592	1.38	200	2.9603	1.0
2.9116	2.07	300	2.8921	1.0
2.1332	2.76	400	1.9718	0.9958
0.8477	3.45	500	0.7813	0.5237
0.4251	4.14	600	0.5166	0.3982
0.3743	4.83	700	0.4400	0.3578
0.4194	5.52	800	0.4077	0.3370
0.23	6.21	900	0.4018	0.3142
0.1554	6.9	1000	0.3623	0.2995
0.1511	7.59	1100	0.3433	0.2697
0.1983	8.28	1200	0.3539	0.2715
0.1443	8.97	1300	0.3622	0.2551
0.0971	9.66	1400	0.3580	0.2519
0.0764	10.34	1500	0.3529	0.2437
0.1203	11.03	1600	0.3455	0.2431
0.0881	11.72	1700	0.3648	0.2415
0.0521	12.41	1800	0.3564	0.2320
0.0434	13.1	1900	0.3485	0.2270
0.0864	13.79	2000	0.3517	0.2228
0.0651	14.48	2100	0.3506	0.2285
0.0423	15.17	2200	0.3428	0.2247
0.0302	15.86	2300	0.3372	0.2198
0.0548	16.55	2400	0.3496	0.2196
0.0674	17.24	2500	0.3407	0.2166
0.0291	17.93	2600	0.3512	0.2171
0.0298	18.62	2700	0.3363	0.2158
0.0419	19.31	2800	0.3493	0.2145
0.046	20.0	2900	0.3457	0.2151

Framework versions

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