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Whisper openai-whisper-large-v3-LoRA32-es_ecu911
This model is a fine-tuned version of openai/whisper-large-v3 on the llamadas ecu9111 segmentos dmarquez dataset. It achieves the following results on the evaluation set:
- Loss: 0.7115
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9042 | 1.0 | 53 | 0.9009 |
| 0.6317 | 2.0 | 106 | 0.6978 |
| 0.5276 | 3.0 | 159 | 0.6820 |
| 0.4666 | 4.0 | 212 | 0.6947 |
| 0.4575 | 5.0 | 265 | 0.7115 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for flima/openai-whisper-large-v3-LoRA32-es_ecu911
Base model
openai/whisper-large-v3