|
--- |
|
language: |
|
- ga |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-medium |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- ymoslem/IWSLT2023-GA-EN |
|
- ymoslem/FLEURS-GA-EN |
|
- ymoslem/BitesizeIrish-GA-EN |
|
- ymoslem/SpokenWords-GA-EN-MTed |
|
model-index: |
|
- name: Whisper Medium GA-EN Speech Translation |
|
results: [] |
|
--- |
|
|
|
<!-- 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 Medium GA-EN Speech Translation |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset. |
|
It achieves the following results on the evaluation set: |
|
- epoch: 0.49 |
|
- eval_bleu: 30.37 |
|
- eval_chrf: 50.78 |
|
- eval_loss: 1.0718 |
|
- eval_runtime: 116.0928 |
|
- eval_samples_per_second: 2.989 |
|
- eval_steps_per_second: 0.19 |
|
- eval_wer: 68.6628 |
|
- step: 1500 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- 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: 2000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
