|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-tiny |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
- wer |
|
- chrf |
|
model-index: |
|
- name: Whisper Tiny GA-EN Speech Translation v.1.4 |
|
results: [] |
|
datasets: |
|
- ymoslem/IWSLT2023-GA-EN |
|
language: |
|
- ga |
|
- en |
|
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 Tiny GA-EN Speech Translation v.1.4 |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
|
The best model (this version) is at checkpoint 500, epoch 7.35, and it achieves the following results on the evaluation set: |
|
- Loss: 2.5784 |
|
- Bleu: 17.0 |
|
- Chrf: 30.42 |
|
- Wer: 85.8622 |
|
|
|
|
|
## 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 |
