metadata
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
Whisper Large-V3 Catalan
This model is a fine-tuned version of 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