README.md

metadata

language:
  - ac
license: apache-2.0
base_model: openai/whisper-small
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - tericlabs
metrics:
  - wer
model-index:
  - name: Whisper base acholi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Sunbird
          type: tericlabs
        metrics:
          - name: Wer
            type: wer
            value: 122.26379794200186

Whisper base acholi

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

• Loss: 2.8895
• Wer: 122.2638

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: 1000
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.2321	3.32	1000	2.9610	140.3181
2.5056	6.64	2000	2.7358	116.9317
2.0671	9.97	3000	2.7957	144.9953
1.7382	13.29	4000	2.8895	122.2638

Framework versions

• Transformers 4.38.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2