detect_language / README.md
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metadata
license: apache-2.0
tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - xtreme_s
metrics:
  - accuracy
base_model: openai/whisper-medium
model-index:
  - name: whisper-medium-fleurs-lang-id
    results: []

Whisper Medium FLEURS Language Identification

This model is a fine-tuned version of openai/whisper-medium on the FLEURS subset of the google/xtreme_s dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8413
  • Accuracy: 0.8805

To reproduce this run, execute the command in run.sh.

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 0
  • 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_ratio: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0152 1.0 8494 0.9087 0.8431
0.0003 2.0 16988 1.0059 0.8460
0.0 3.0 25482 0.8413 0.8805

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1
  • Datasets 2.9.0
  • Tokenizers 0.13.2