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---
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small - Greek (el)
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 el
type: mozilla-foundation/common_voice_11_0
config: el
split: test
args: el
metrics:
- name: Wer
type: wer
value: 25.696508172362552
---
<!-- 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 - Greek (el)
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 el dataset
for translation from Greek to English.
It achieves the following results on the evaluation set:
- Loss: 0.4642
- Wer: 25.6965
## Model description
This model was finetuned with the encoder frozen. Only the decoder weights have been changed by this training run.
## Intended uses & limitations
The purpose of this model was to understand how the freezing of a part of the model might affect learning, in an effort to assess the feasibility of enabling adapters.
## Training and evaluation data
The training was performed by streaming interleaved train+eval spits of the greek (el) subset of mozilla-foundation/common_voice_11_0 (el).
The test set was similarly used for validation.
## Training procedure
The script used to perform the training is included in the files of this space:
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0032 | 18.01 | 1000 | 0.4642 | 25.6965 |
| 0.0006 | 37.01 | 2000 | 0.5369 | 26.4395 |
| 0.0003 | 56.01 | 3000 | 0.5703 | 26.3187 |
| 0.0002 | 75.0 | 4000 | 0.5913 | 26.4302 |
| 0.0001 | 94.0 | 5000 | 0.5996 | 26.4952 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.12.1
|