File size: 5,266 Bytes
ad9baae fe010a1 ad9baae fe010a1 80d1499 ad9baae fe010a1 80d1499 ad9baae fe010a1 ad9baae 80d1499 65b98c7 80d1499 ad9baae 80d1499 ad9baae fe010a1 80d1499 fe010a1 ad9baae 80d1499 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 |
---
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
metrics:
- bleu
- wer
- chrf
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
type: ymoslem/IWSLT2023-GA-EN
metrics:
- name: Bleu
type: bleu
value: 26.85
- name: Wer
type: wer
value: 73.52543899144528
library_name: transformers
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, and SpokenWords datasets.
The best model checkpoint (this version) is at step 3400, epoch 3.67, and it achieves the following results on the evaluation set:
- Loss: 1.5752
- Bleu: 30.77
- Chrf: 46.43
- Wer: 64.6556
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Experiment
- language=English
- +more steps
### 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:-----:|:-----:|:---------------:|:--------:|
| 2.4954 | 0.11 | 100 | 3.7 | 18.03 | 2.1286 | 179.7839 |
| 2.045 | 0.22 | 200 | 12.65 | 25.53 | 1.8146 | 100.9005 |
| 1.7928 | 0.32 | 300 | 13.78 | 30.2 | 1.7253 | 101.9811 |
| 1.6615 | 0.43 | 400 | 15.8 | 31.88 | 1.6834 | 92.5259 |
| 1.4491 | 0.54 | 500 | 15.61 | 36.27 | 1.5971 | 107.3841 |
| 1.2074 | 0.65 | 600 | 19.92 | 36.31 | 1.5939 | 84.3314 |
| 1.2308 | 0.76 | 700 | 20.37 | 38.72 | 1.5234 | 84.8267 |
| 1.107 | 0.86 | 800 | 21.35 | 37.87 | 1.5460 | 82.8906 |
| 0.9491 | 0.97 | 900 | 21.06 | 40.74 | 1.5161 | 82.5754 |
| 0.384 | 1.08 | 1000 | 23.24 | 41.98 | 1.4927 | 82.2152 |
| 0.362 | 1.19 | 1100 | 23.19 | 42.24 | 1.5567 | 80.2792 |
| 0.3756 | 1.29 | 1200 | 27.83 | 43.8 | 1.5265 | 69.2481 |
| 0.3401 | 1.4 | 1300 | 21.79 | 41.66 | 1.5522 | 92.3908 |
| 0.3346 | 1.51 | 1400 | 24.61 | 42.15 | 1.5085 | 75.4615 |
| 0.3101 | 1.62 | 1500 | 26.67 | 43.41 | 1.4933 | 70.7789 |
| 0.3231 | 1.73 | 1600 | 27.95 | 42.82 | 1.4979 | 68.3026 |
| 0.2665 | 1.83 | 1700 | 28.5 | 43.76 | 1.4977 | 68.1225 |
| 0.2704 | 1.94 | 1800 | 28.15 | 43.87 | 1.5063 | 68.8429 |
| 0.0769 | 2.05 | 1900 | 25.76 | 43.22 | 1.5162 | 77.6227 |
| 0.0597 | 2.16 | 2000 | 25.04 | 43.15 | 1.5216 | 79.0635 |
| 0.0743 | 2.27 | 2100 | 27.85 | 44.43 | 1.5313 | 68.3926 |
| 0.0878 | 2.37 | 2200 | 27.54 | 43.96 | 1.5495 | 68.3476 |
| 0.0712 | 2.48 | 2300 | 28.28 | 44.39 | 1.5355 | 65.8712 |
| 0.0789 | 2.59 | 2400 | 28.64 | 44.75 | 1.5277 | 65.7812 |
| 0.073 | 2.7 | 2500 | 29.09 | 44.65 | 1.5327 | 65.7812 |
| 0.073 | 2.8 | 2600 | 25.26 | 43.44 | 1.5304 | 78.2981 |
| 0.0697 | 2.91 | 2700 | 25.71 | 43.02 | 1.5460 | 78.4782 |
| 0.0398 | 3.02 | 2800 | 28.26 | 44.71 | 1.5580 | 72.8501 |
| 0.0302 | 3.13 | 2900 | 30.25 | 45.46 | 1.5688 | 66.1414 |
| 0.0424 | 3.24 | 3000 | 29.88 | 45.21 | 1.5693 | 66.0964 |
| 0.0397 | 3.34 | 3100 | 30.01 | 45.85 | 1.5934 | 65.6911 |
| 0.0346 | 3.45 | 3200 | 30.2 | 45.8 | 1.5818 | 65.8262 |
| 0.032 | 3.56 | 3300 | 29.81 | 46.5 | 1.5823 | 66.7267 |
| 0.0348 | 3.67 | 3400 | 30.77 | 46.43 | 1.5752 | 64.6556 |
| 0.0277 | 3.78 | 3500 | 30.3 | 46.02 | 1.5791 | 64.6105 |
| 0.0364 | 3.88 | 3600 | 29.92 | 45.38 | 1.5895 | 65.0608 |
| 0.0398 | 3.99 | 3700 | 27.79 | 44.59 | 1.6167 | 68.2575 |
| 0.0152 | 4.1 | 3800 | 28.42 | 44.83 | 1.6241 | 67.5822 |
| 0.0201 | 4.21 | 3900 | 29.02 | 45.11 | 1.6243 | 67.4921 |
| 0.0168 | 4.31 | 4000 | 26.85 | 44.41 | 1.6195 | 73.5254 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |