metadata

license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - arrow
metrics:
  - wer
model-index:
  - name: whisper-small-indian_eng
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: arrow
          type: arrow
          config: default
          split: validation
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 15.730337078651685

whisper-small-indian_eng

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

Loss: 0.7367
Wer: 15.7303

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: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 25
training_steps: 200
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5156	10.0	50	1.0266	19.1011
0.171	20.0	100	0.7371	16.8539
0.0018	30.0	150	0.6975	15.7303
0.0004	40.0	200	0.7367	15.7303

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.0.0
Datasets 2.16.1
Tokenizers 0.19.1