metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Large Pashto
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs ps_af
          type: google/fleurs
          config: ps_af
          split: test
          args: ps_af
        metrics:
          - name: Wer
            type: wer
            value: 54.06850588964662

Whisper Large Pashto

This model is a fine-tuned version of openai/whisper-large-v2 on the google/fleurs ps_af dataset. It achieves the following results on the evaluation set:

Loss: 0.8623
Wer: 54.0685

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: 3e-07
train_batch_size: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 700
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.2281	16.59	100	1.0951	69.3118
0.7529	33.3	200	0.8693	57.5635
0.5372	49.89	300	0.8399	54.7350
0.4398	66.59	400	0.8623	54.0685
0.3244	83.3	500	0.9098	54.7505
0.238	99.89	600	0.9607	55.3782
0.2014	116.59	700	1.0077	55.9206

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2