README.md

metadata

language:
  - as
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Medium Assamese - Drishti Sharma
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: as
          split: test
          args: as
        metrics:
          - name: Wer
            type: wer
            value: 30.650219527493206

Whisper Small Assamese - Drishti Sharma

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5164
• Wer: 30.6502

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
• gradient_accumulation_steps: 4
• 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: 150
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.1539	3.02	50	0.7835	89.0863
0.2089	7.0	100	0.3041	37.7378
0.0428	10.02	150	0.3760	33.9118
0.0141	14.01	200	0.4400	31.6538
0.0059	17.02	250	0.4472	31.2774
0.0022	21.01	300	0.4696	31.0475
0.0005	24.03	350	0.5032	31.2983
0.0003	28.02	400	0.5051	30.7129
0.0003	32.0	450	0.5137	30.7338
0.0003	35.02	500	0.5164	30.6502

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu116
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2