transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer ca dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-large-v3 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ca
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V3 Catalan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 ca
      type: mozilla-foundation/common_voice_13_0
      config: ca
      split: test
      args: ca
    metrics:
    - name: Wer
      type: wer
      value: 5.971420405830237
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Large-V3 Catalan

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_13_0 ca dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2783
- Wer: 5.9714

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0988        | 1.95  | 1000  | 0.1487          | 6.5619 |
| 0.025         | 3.91  | 2000  | 0.1676          | 6.3155 |
| 0.0105        | 5.86  | 3000  | 0.1871          | 6.4035 |
| 0.0047        | 7.81  | 4000  | 0.1973          | 6.4870 |
| 0.0061        | 9.77  | 5000  | 0.2086          | 6.4836 |
| 0.0034        | 11.72 | 6000  | 0.2172          | 6.6442 |
| 0.0036        | 13.67 | 7000  | 0.2205          | 6.4041 |
| 0.002         | 15.62 | 8000  | 0.2214          | 6.4350 |
| 0.0011        | 17.58 | 9000  | 0.2339          | 6.1943 |
| 0.0009        | 19.53 | 10000 | 0.2388          | 6.2921 |
| 0.0011        | 21.48 | 11000 | 0.2327          | 6.2515 |
| 0.0003        | 23.44 | 12000 | 0.2472          | 6.2052 |
| 0.0012        | 25.39 | 13000 | 0.2382          | 6.2892 |
| 0.0001        | 27.34 | 14000 | 0.2550          | 5.9949 |
| 0.0006        | 29.3  | 15000 | 0.2574          | 6.3607 |
| 0.0001        | 31.25 | 16000 | 0.2584          | 6.0143 |
| 0.0001        | 33.2  | 17000 | 0.2686          | 5.9486 |
| 0.0           | 35.16 | 18000 | 0.2736          | 5.9194 |
| 0.0           | 37.11 | 19000 | 0.2768          | 5.9646 |
| 0.0           | 39.06 | 20000 | 0.2783          | 5.9714 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
