README.md

metadata

language:
  - ga
  - en
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - ymoslem/IWSLT2023-GA-EN
  - ymoslem/FLEURS-GA-EN
  - ymoslem/BitesizeIrish-GA-EN
  - ymoslem/SpokenWords-GA-EN-MTed
model-index:
  - name: Whisper Medium GA-EN Speech Translation
    results: []

Whisper Medium GA-EN Speech Translation

This model is a fine-tuned version of openai/whisper-medium on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset. It achieves the following results on the evaluation set:

• epoch: 0.49
• eval_bleu: 30.37
• eval_chrf: 50.78
• eval_loss: 1.0718
• eval_runtime: 116.0928
• eval_samples_per_second: 2.989
• eval_steps_per_second: 0.19
• eval_wer: 68.6628
• step: 1500

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.03
• training_steps: 2000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.39.3
• Pytorch 2.0.1+cu118
• Datasets 2.18.0
• Tokenizers 0.15.2