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rohitp1/
Nystrom-W2V2-100hrs-take-4-unfreeze-extractor

Name: Nystrom-W2V2-100hrs-take-4-unfreeze-extractor
Availability: InStock

transformers

pytorch

wav2vec2

generated_from_trainer

endpoints_compatible

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Nystrom-W2V2-100hrs-take-4-unfreeze-extractor

This model is a fine-tuned version of rohitp1/Nystrom-W2V2-100hrs-take-3 on the None dataset. It achieves the following results on the evaluation set:

Loss: 27.1839
Wer: 0.0915

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: 0.0005
train_batch_size: 4
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 64
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.2
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
30.9159	9.01	1000	27.2422	0.1205
47.7101	18.02	2000	25.0538	0.1366
61.5118	27.03	3000	25.3063	0.1343
57.2966	36.04	4000	25.0429	0.1276
50.7161	45.04	5000	27.2507	0.1235
43.7605	54.05	6000	25.9086	0.1145
36.8698	63.06	7000	26.4890	0.1085
31.0921	72.07	8000	26.9372	0.1021
26.4249	81.08	9000	27.8031	0.0961
23.336	90.09	10000	27.2129	0.0928
22.2249	99.1	11000	27.1839	0.0915

Framework versions

Transformers 4.24.0
Pytorch 1.12.1
Datasets 2.7.1
Tokenizers 0.11.0

rohitp1/Nystrom-W2V2-100hrs-take-4-unfreeze-extractor

Nystrom-W2V2-100hrs-take-4-unfreeze-extractor

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

rohitp1/
Nystrom-W2V2-100hrs-take-4-unfreeze-extractor