nilc-nlp

psst-model-8e-1s-lp3200hz

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README

License: apache-2.0

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 664
training_steps: 9480

Training results

Table with columns: Training Loss, Epoch, Step, Validation Loss, Wer, Iu F1, Iu Tp, Iu Fp, Iu Fn
Training Loss	Epoch	Step	Validation Loss	Wer	Iu F1	Iu Tp	Iu Fp	Iu Fn
1.0142	1.0	1185	0.5133	0.2418	0.7429	468	216	108
0.6599	2.0	2370

Framework versions

Transformers 5.6.2
Pytorch 2.6.0+cu124
Datasets 2.21.0
Tokenizers 0.22.2

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Model Details

Model Provider

nilc-nlp

Model Tree

Base

openai/whisper-large-v3

Fine-tuned

this model

Input Modalities

Audio

Output Modalities

Text

Supported Functionality

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README

License: apache-2.0

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 664
training_steps: 9480

Training results

Table with columns: Training Loss, Epoch, Step, Validation Loss, Wer, Iu F1, Iu Tp, Iu Fp, Iu Fn
Training Loss	Epoch	Step	Validation Loss	Wer	Iu F1	Iu Tp	Iu Fp	Iu Fn
1.0142	1.0	1185	0.5133	0.2418	0.7429	468	216	108
0.6599	2.0	2370

Framework versions

Transformers 5.6.2
Pytorch 2.6.0+cu124
Datasets 2.21.0
Tokenizers 0.22.2