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Whisper openai-whisper-large-LoRA32-es_ecu911
This model is a fine-tuned version of openai/whisper-large on the llamadas ecu9111 segmentos dmarquez dataset. It achieves the following results on the evaluation set:
- Loss: 0.7446
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 |
|---|---|---|---|
| 1.253 | 1.0 | 53 | 1.0113 |
| 0.7443 | 2.0 | 106 | 0.7473 |
| 0.6761 | 3.0 | 159 | 0.7312 |
| 0.6156 | 4.0 | 212 | 0.7381 |
| 0.5384 | 5.0 | 265 | 0.7446 |
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 UDA-LIDI/openai-whisper-large-LoRA32-es_ecu911_adapter
Base model
openai/whisper-large