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Niccogrillo/
wav2vec2-base-CALLCENTER

Name: wav2vec2-base-CALLCENTER
Availability: InStock

automatic-speech-recognition

generated_from_trainer

endpoints_compatible

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wav2vec2-base-CALLCENTER

This model is a fine-tuned version of Niccogrillo/wav2vec2-base-CALLCENTER on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4605
Wer: 0.2139

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
6.9258	0.41	500	2.6959	0.9996
0.7059	0.82	1000	0.6081	0.2841
0.1633	1.22	1500	0.5037	0.2302
0.2361	1.63	2000	0.4207	0.2206
0.2289	2.04	2500	0.4433	0.2184
0.1794	2.45	3000	0.4648	0.2172
0.1827	2.86	3500	0.4592	0.2151
0.1844	3.27	4000	0.4507	0.2143
0.1723	3.67	4500	0.4561	0.2143
0.1762	4.08	5000	0.4633	0.2143
0.1762	4.49	5500	0.4610	0.2140
0.1552	4.9	6000	0.4605	0.2139

Framework versions

Transformers 4.30.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.13.3