whisper-large-v2-finetuning-3
This model is a fine-tuned version of guilhermebastos96/whisper-large-v2-finetuning-2 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2959
- Wer: 7.9254
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: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0365 | 0.5089 | 1000 | 0.2219 | 12.8233 |
0.0154 | 1.0178 | 2000 | 0.2462 | 9.3545 |
0.0255 | 1.5267 | 3000 | 0.2492 | 9.2442 |
0.0178 | 2.0356 | 4000 | 0.2386 | 9.3401 |
0.0121 | 2.5445 | 5000 | 0.2447 | 8.9741 |
0.0051 | 3.0534 | 6000 | 0.2619 | 8.8478 |
0.0034 | 3.5623 | 7000 | 0.2634 | 8.3427 |
0.0014 | 4.0712 | 8000 | 0.2776 | 8.0597 |
0.001 | 4.5802 | 9000 | 0.2961 | 8.0022 |
0.0006 | 5.0891 | 10000 | 0.2959 | 7.9254 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1
- Downloads last month
- 10
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for guilhermebastos96/whisper-large-v2-finetuning-3
Base model
openai/whisper-large-v2
Finetuned
this model