README.md

metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: whisper-tiny-finetuned-minds14-enUS_2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: PolyAI/minds14
          type: PolyAI/minds14
        metrics:
          - name: Wer
            type: wer
            value: 0.33943329397874855

whisper-tiny-finetuned-minds14-enUS_2

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

• Loss: 0.7508
• Wer Ortho: 0.3356
• Wer: 0.3394
• Cer: 0.2613
• Cer Ortho: 0.2623

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• 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 Ortho	Wer	Cer	Cer Ortho
0.0136	7.14	100	0.6142	0.3362	0.3388	0.2587	0.2614
0.0009	14.29	200	0.6704	0.3288	0.3300	0.2515	0.2534
0.0011	21.43	300	0.6858	0.3054	0.3093	0.2363	0.2374
0.0005	28.57	400	0.7081	0.3455	0.3477	0.2699	0.2711
0.0004	35.71	500	0.7191	0.3467	0.3501	0.2727	0.2736
0.0001	42.86	600	0.7337	0.3405	0.3447	0.2652	0.2662
0.0001	50.0	700	0.7418	0.3393	0.3430	0.2636	0.2645
0.0001	57.14	800	0.7466	0.3387	0.3424	0.2634	0.2644
0.0001	64.29	900	0.7496	0.3350	0.3388	0.2604	0.2614
0.0001	71.43	1000	0.7508	0.3356	0.3394	0.2613	0.2623

Framework versions

• Transformers 4.32.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3