wav2vec2-base-CALLCENTER

Niccogrillo/wav2vec2-base-CALLCENTER

wav2vec2-base-CALLCENTER is a automatic speech recognition model from Niccogrillo. Use it when you need speech turned into text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
Model type: wav2vec2
Access: Public
Created: Apr 29, 2024
Updated: May 2, 2024
SHA: 3cc2fe02

Model card

From the Hugging Face model README

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

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Apr 29, 2024
Updated: May 2, 2024