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---
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0,google/fleurs
metrics:
- wer
model-index:
- name: Whisper small Greek Farsipal and El Greco
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr
type: mozilla-foundation/common_voice_11_0,google/fleurs
config: el
split: None
metrics:
- name: Wer
type: wer
value: 17.199108469539375
---
<!-- 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 Farsioal and El Greco
This model is a fine-tuned version of [emilios/whisper-sm-el-farsipal-e4](https://huggingface.co/emilios/whisper-sm-el-farsipal-e4) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4871
- Wer: 17.1991
## 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: 1e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1259 | 2.49 | 1000 | 0.4834 | 18.3692 |
| 0.1002 | 4.49 | 2000 | 0.4604 | 17.8027 |
| 0.1096 | 6.98 | 3000 | 0.4553 | 17.8770 |
| 0.0885 | 9.46 | 4000 | 0.4551 | 17.9606 |
| 0.0675 | 11.95 | 5000 | 0.4631 | 17.9049 |
| 0.0675 | 14.44 | 6000 | 0.4619 | 17.9049 |
| 0.0645 | 16.93 | 7000 | 0.4678 | 17.6727 |
| 0.0535 | 19.41 | 8000 | 0.4685 | 17.6634 |
| 0.039 | 21.49 | 9000 | 0.4746 | 17.6727 |
| 0.0447 | 23.98 | 10000 | 0.4761 | 17.6634 |
| 0.0393 | 26.46 | 11000 | 0.4792 | 17.7656 |
| 0.0308 | 28.95 | 12000 | 0.4851 | 17.8678 |
| 0.0301 | 31.44 | 13000 | 0.4846 | 17.4499 |
| 0.031 | 33.93 | 14000 | 0.4849 | 17.8306 |
| 0.0263 | 36.41 | 15000 | 0.4880 | 17.6170 |
| 0.0256 | 38.9 | 16000 | 0.4871 | 17.1991 |
| 0.0236 | 41.39 | 17000 | 0.4883 | 17.2641 |
| 0.0195 | 43.88 | 18000 | 0.4880 | 17.5706 |
| 0.0193 | 46.36 | 19000 | 0.4993 | 17.7285 |
| 0.0161 | 48.85 | 20000 | 0.4968 | 17.8306 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 2.0.0.dev20221216+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|