File size: 2,874 Bytes
bbc0fa9 30f6e1e bbc0fa9 30f6e1e bbc0fa9 30f6e1e bbc0fa9 30f6e1e bbc0fa9 30f6e1e bbc0fa9 30f6e1e bbc0fa9 |
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 |
---
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: 23.1
- name: Wer
type: wer
value: 82.89058982440342
---
<!-- 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, SpokenWords, Tatoeba, and Wikimedia dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2172
- Bleu: 23.1
- Chrf: 42.54
- Wer: 82.8906
## 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: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.8459 | 0.07 | 100 | 2.0769 | 3.28 | 18.43 | 149.0770 |
| 2.3328 | 0.13 | 200 | 1.8396 | 4.5 | 22.06 | 207.7443 |
| 2.1669 | 0.2 | 300 | 1.6215 | 14.6 | 30.8 | 89.1941 |
| 1.8606 | 0.26 | 400 | 1.5030 | 14.65 | 33.33 | 92.4358 |
| 1.7255 | 0.33 | 500 | 1.4085 | 14.9 | 35.14 | 103.8271 |
| 1.5855 | 0.39 | 600 | 1.3587 | 15.78 | 35.02 | 103.0617 |
| 1.5875 | 0.46 | 700 | 1.2986 | 25.3 | 41.37 | 69.4732 |
| 1.44 | 0.53 | 800 | 1.2575 | 25.78 | 42.23 | 70.0585 |
| 1.3317 | 0.59 | 900 | 1.2338 | 23.24 | 41.64 | 79.1085 |
| 1.3166 | 0.66 | 1000 | 1.2172 | 23.1 | 42.54 | 82.8906 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|