fineturning-with-pretraining-2 – AI Model by Aviral2412 | AlphaNeural AI

You can deploy this model and start earning money today!

Aviral2412/
fineturning-with-pretraining-2

like

0

automatic-speech-recognition

generated_from_trainer

common_voice_1_0

Aviral2412/mini_model

endpoints_compatible

Views

No views yet

fineturning-with-pretraining-2

This model is a fine-tuned version of Aviral2412/mini_model on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:

Loss: 2.6209
Wer: 1.0047

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: 0.0009
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 35
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4746	4.29	500	2.5056	1.0013
2.4704	8.58	1000	2.4840	1.0013
2.4346	12.88	1500	2.4060	1.0013
2.3825	17.17	2000	2.4998	1.0014
2.2596	21.46	2500	2.6122	1.0019
2.1902	25.75	3000	2.6619	1.0027
2.1675	30.04	3500	2.6117	1.0048
2.143	34.33	4000	2.6209	1.0047

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2