README.md

metadata

language:
  - ga
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: whisper-large-v2-Irish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: ga-IE
          split: test
          args: ga-IE
        metrics:
          - name: Wer
            type: wer
            value: 34.26248548199768
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: FLEURS
          type: mozilla-foundation/common_voice_11_0
        metrics:
          - name: Wer
            type: wer
            value: null

whisper-large-v2-Irish

This model is a fine-tuned version of kpriyanshu256/whisper-large-v2-cy-500-32-1e-05 on the Common Voice 11.0 and the FLEURS datasets. It achieves the following results on the evaluation set:

• Loss: 0.7879
• Wer: 34.2625

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
• distributed_type: multi-GPU
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3768	0.25	250	0.7143	39.4890
0.1498	1.15	500	0.7663	35.8014
0.0907	2.05	750	0.7730	35.2497
0.045	2.3	1000	0.7879	34.2625

Framework versions

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