metadata

license: apache-2.0
tags:
  - automatic-speech-recognition
  - timit_asr
  - generated_from_trainer
datasets:
  - timit_asr
model-index:
  - name: distilhubert-timit
    results: []

distilhubert-timit

This model is a fine-tuned version of ntu-spml/distilhubert on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

Loss: 1.3601
Wer: 0.6776

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
5.4447	0.69	100	4.9546	1.0
2.9499	1.38	200	2.9519	1.0
2.8989	2.07	300	2.8624	1.0
2.2076	2.76	400	2.1089	1.0008
1.4186	3.45	500	1.4112	0.9165
0.9951	4.14	600	1.1378	0.7701
0.9754	4.83	700	1.0152	0.7274
0.9364	5.52	800	0.9619	0.7011
0.6557	6.21	900	0.9144	0.6868
0.5681	6.9	1000	0.8899	0.6683
0.66	7.59	1100	0.8992	0.6654
0.6144	8.28	1200	0.9299	0.6898
0.4099	8.97	1300	0.9510	0.6674
0.3384	9.66	1400	0.9598	0.6612
0.3163	10.34	1500	0.9954	0.6612
0.4204	11.03	1600	1.0164	0.6607
0.1932	11.72	1700	1.0637	0.6658
0.1449	12.41	1800	1.1190	0.6652
0.1803	13.1	1900	1.1260	0.6689
0.328	13.79	2000	1.2186	0.6751
0.0838	14.48	2100	1.2591	0.6909
0.0766	15.17	2200	1.2529	0.6780
0.0956	15.86	2300	1.2537	0.6668
0.2339	16.55	2400	1.3210	0.6797
0.0431	17.24	2500	1.3241	0.6781
0.0508	17.93	2600	1.3184	0.6683
0.0616	18.62	2700	1.3728	0.6889
0.1608	19.31	2800	1.3572	0.6771
0.0378	20.0	2900	1.3601	0.6776

Framework versions

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