metadata

language:
  - ta
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Base Ta - Bharat Ramanathan
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: ta
          split: test
        metrics:
          - type: wer
            value: 15.78
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: ta_in
          split: test
        metrics:
          - type: wer
            value: 20.41
            name: WER

Whisper Base Ta - Bharat Ramanathan

This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2269
Wer: 21.7243

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: 64
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: 1000
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5559	0.1	1000	0.3963	35.3308
0.3891	0.2	2000	0.3146	29.1511
0.3425	0.3	3000	0.2834	25.5930
0.3108	0.1	4000	0.2669	24.7191
0.2866	0.1	5000	0.2596	25.0936
0.2697	0.2	6000	0.2507	24.5943
0.2421	0.05	6500	0.2411	23.0395
0.2425	0.1	7000	0.2370	23.3804
0.2404	0.15	7500	0.2333	22.7959
0.2381	0.2	8000	0.2311	22.9420
0.2429	0.25	8500	0.2305	22.0166
0.2402	0.3	9000	0.2284	22.1140
0.2377	0.35	9500	0.2271	22.0653
0.2389	0.4	10000	0.2269	21.7243

Framework versions

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