README.md

metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
metrics:
  - bleu
  - wer
model-index:
  - name: Whisper Tiny GA-EN Speech Translation v.1.4
    results: []
datasets:
  - ymoslem/IWSLT2023-GA-EN
language:
  - ga
  - en

Whisper Tiny GA-EN Speech Translation v.1.4

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

• Loss: 2.7420
• Bleu: 14.71
• Chrf: 30.02
• Wer: 95.7226

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Experiment

As this is a translation task into English, use language="English"

tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-tiny",
                                             cache_dir=cache_dir,
                                             language="english",
                                             task="translate")

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 128
• eval_batch_size: 128
• 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: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Chrf	Wer
0.8117	1.47	100	2.1773	8.81	24.15	119.9910
0.3555	2.94	200	2.2596	11.81	27.7	110.8510
0.0872	4.41	300	2.4108	12.89	28.57	110.5808
0.063	5.88	400	2.5306	12.67	27.78	107.1139
0.034	7.35	500	2.5784	17.0	30.42	85.8622
0.0349	8.82	600	2.6201	16.64	29.98	86.8978
0.0198	10.29	700	2.7151	16.0	30.04	88.2936
0.0134	11.76	800	2.7159	14.16	30.03	105.0878
0.0088	13.24	900	2.7369	14.61	29.32	94.3269
0.0056	14.71	1000	2.7420	14.71	30.02	95.7226

Framework versions

• Transformers 4.39.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2