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---
language:
- ca
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Catalan
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ca
type: mozilla-foundation/common_voice_11_0
args: 'config: ml, split: test'
metrics:
- name: Wer
type: wer
value: 8.569471791798646
---
<!-- 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 Catalan
This is an automatic speech recognition model that also does punctuation and casing. Vegeu [projecte de millora dels models Whisper](https://www.softcatala.org/projectes/millora-del-catala-dels-models-del-reconeixement-de-la-parla-whisper/) (Catalan).
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 ca dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1980
- Wer: 8.5695
## 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-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2128 | 0.1 | 2000 | 0.2644 | 13.0303 |
| 0.1361 | 1.1 | 4000 | 0.2300 | 10.9568 |
| 0.0658 | 2.1 | 6000 | 0.2376 | 11.2810 |
| 0.102 | 3.09 | 8000 | 0.2156 | 9.8730 |
| 0.0706 | 4.09 | 10000 | 0.2126 | 9.6179 |
| 0.0428 | 5.09 | 12000 | 0.2178 | 9.3405 |
| 0.0503 | 6.09 | 14000 | 0.2109 | 9.1356 |
| 0.0778 | 7.08 | 16000 | 0.2058 | 9.2001 |
| 0.0082 | 8.08 | 18000 | 0.2173 | 8.9941 |
| 0.0994 | 9.08 | 20000 | 0.1980 | 8.5695 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 2.7.1
- Tokenizers 0.13.2
|