--- 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](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