|
--- |
|
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 |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 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 |
|
|
