metadata

base_model: openai/whisper-medium
datasets:
  - generator
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: whisper-medium-sb-lug-eng-v2
    results: []

whisper-medium-sb-lug-eng-v2

This model is a fine-tuned version of openai/whisper-medium on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.1255
Wer Lug: 0.124
Wer Eng: 0.171
Wer Mean: 0.147
Cer Lug: 0.028
Cer Eng: 0.164
Cer Mean: 0.096

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: 16
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: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Lug	Wer Eng	Wer Mean	Cer Lug	Cer Eng	Cer Mean
0.7222	0.1	500	0.2662	0.391	0.146	0.268	0.085	0.104	0.095
0.5452	0.2	1000	0.1894	0.223	0.058	0.141	0.05	0.034	0.042
0.4172	0.3	1500	0.1764	0.199	0.276	0.238	0.043	0.269	0.156
0.3949	0.4	2000	0.1583	0.177	0.035	0.106	0.039	0.017	0.028
0.3626	0.5	2500	0.1508	0.153	0.157	0.155	0.035	0.122	0.078
0.3467	0.6	3000	0.1397	0.14	0.258	0.199	0.033	0.213	0.123
0.3443	0.7	3500	0.1333	0.139	0.044	0.092	0.032	0.027	0.029
0.3169	0.8	4000	0.1297	0.129	0.027	0.078	0.029	0.011	0.02
0.3276	0.9	4500	0.1264	0.124	0.086	0.105	0.028	0.058	0.043
0.317	1.0	5000	0.1255	0.124	0.171	0.147	0.028	0.164	0.096

Framework versions

Transformers 4.42.4
Pytorch 2.2.0
Datasets 2.20.0
Tokenizers 0.19.1