metadata
language:
- ga
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- ymoslem/IWSLT2023-GA-EN
- ymoslem/FLEURS-GA-EN
- ymoslem/BitesizeIrish-GA-EN
- ymoslem/SpokenWords-GA-EN-MTed
- ymoslem/Tatoeba-Speech-Irish
- ymoslem/Wikimedia-Speech-Irish
metrics:
- bleu
- wer
model-index:
- name: Whisper Small GA-EN Speech Translation
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia
type: ymoslem/IWSLT2023-GA-EN
metrics:
- name: Bleu
type: bleu
value: 27.57
- name: Wer
type: wer
value: 70.64385411976588
Whisper Small GA-EN Speech Translation
This model is a fine-tuned version of openai/whisper-small on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset. The best model checkpoint (this version) based on ChrF is at step 2500, epoch 1.64, and it achieves the following results on the evaluation set:
- Loss: 1.1898
- Bleu: 26.61
- Chrf: 47.8
- Wer: 71.1391
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: 32
- 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: 0.03
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
|---|---|---|---|---|---|---|
| 2.6685 | 0.07 | 100 | 5.05 | 20.18 | 2.0544 | 139.8919 |
| 2.4028 | 0.13 | 200 | 12.29 | 29.72 | 1.7367 | 95.5425 |
| 2.1231 | 0.2 | 300 | 14.33 | 30.77 | 1.6141 | 101.3958 |
| 1.9192 | 0.26 | 400 | 16.86 | 35.65 | 1.4778 | 91.0851 |
| 1.7129 | 0.33 | 500 | 16.77 | 37.53 | 1.3811 | 93.8766 |
| 1.5398 | 0.39 | 600 | 18.85 | 39.0 | 1.3427 | 90.2296 |
| 1.4257 | 0.46 | 700 | 25.73 | 43.3 | 1.2784 | 70.3287 |
| 1.3044 | 0.53 | 800 | 25.43 | 44.33 | 1.2274 | 72.3548 |
| 1.2626 | 0.59 | 900 | 25.09 | 44.62 | 1.1875 | 72.6249 |
| 1.2801 | 0.66 | 1000 | 25.68 | 45.53 | 1.1571 | 71.0491 |
| 1.2876 | 0.72 | 1100 | 20.62 | 41.49 | 1.2193 | 85.8622 |
| 1.2609 | 0.79 | 1200 | 29.47 | 45.04 | 1.2079 | 65.2859 |
| 1.187 | 0.85 | 1300 | 24.65 | 43.73 | 1.2086 | 72.9851 |
| 1.0342 | 0.92 | 1400 | 30.34 | 47.62 | 1.1766 | 64.3854 |
| 1.0519 | 0.98 | 1500 | 29.39 | 47.69 | 1.1425 | 64.9707 |
| 0.5473 | 1.05 | 1600 | 28.02 | 46.27 | 1.1842 | 67.6722 |
| 0.4886 | 1.12 | 1700 | 26.62 | 46.37 | 1.1845 | 76.4971 |
| 0.4354 | 1.18 | 1800 | 23.63 | 45.16 | 1.1621 | 86.1324 |
| 0.4709 | 1.25 | 1900 | 27.86 | 47.3 | 1.1544 | 73.7506 |
| 0.4802 | 1.31 | 2000 | 30.25 | 48.12 | 1.1571 | 64.9707 |
| 0.4565 | 1.38 | 2100 | 24.75 | 44.7 | 1.2095 | 77.4426 |
| 0.4797 | 1.44 | 2200 | 28.46 | 46.03 | 1.2051 | 67.1769 |
| 0.423 | 1.51 | 2300 | 28.34 | 47.65 | 1.2079 | 68.6177 |
| 0.4254 | 1.58 | 2400 | 27.78 | 46.01 | 1.2251 | 67.8523 |
| 0.4493 | 1.64 | 2500 | 26.61 | 47.8 | 1.1898 | 71.1391 |
| 0.3614 | 1.71 | 2600 | 30.08 | 47.25 | 1.2079 | 64.2954 |
| 0.4052 | 1.77 | 2700 | 30.88 | 47.44 | 1.1975 | 64.2053 |
| 0.3541 | 1.84 | 2800 | 28.4 | 46.02 | 1.2006 | 70.2837 |
| 0.3736 | 1.9 | 2900 | 30.82 | 47.52 | 1.1906 | 64.1153 |
| 0.3326 | 1.97 | 3000 | 27.57 | 46.72 | 1.1870 | 70.6439 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2