metadata

base_model: distil-whisper/distil-large-v3
datasets:
  - Gabi00/english-mistakes
language:
  - eng
library_name: peft
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: Whisper Small Eng - Gabriel Mora
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: English-mistakes
          type: Gabi00/english-mistakes
          config: default
          split: validation
          args: 'config: eng, split: test'
        metrics:
          - type: wer
            value: 18.4360567877302
            name: Wer

Whisper Small Eng - Gabriel Mora

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

Loss: 0.6839
Wer: 18.4361

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: 28
eval_batch_size: 28
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: 100000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.5189	0.4444	500	1.1913	25.9108
1.1727	0.8889	1000	0.9531	24.5396
1.1341	1.3333	1500	0.8688	22.2761
1.0152	1.7778	2000	0.8174	20.8792
1.0589	2.2222	2500	0.7855	20.7595
0.9793	2.6667	3000	0.7611	22.2846
0.9594	3.1111	3500	0.7442	20.3860
1.0031	3.5556	4000	0.7303	18.5045
0.9525	4.0	4500	0.7199	18.1054
0.8729	4.4444	5000	0.7105	19.3170
1.0031	4.8889	5500	0.7028	19.7446
0.9273	5.3333	6000	0.6966	19.7189
0.9174	5.7778	6500	0.6896	18.4475
0.8842	6.2222	7000	0.6839	18.4361

Framework versions

PEFT 0.11.1
Transformers 4.42.4
Pytorch 2.1.0+cu118
Datasets 2.20.0
Tokenizers 0.19.1