Fauna-v0.7 - Rootflo
This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0558
- Wer: 60.7190
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-06
- train_batch_size: 72
- eval_batch_size: 96
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 576
- total_eval_batch_size: 384
- optimizer: Use adamw_bnb_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0301 | 1.0695 | 500 | 0.0498 | 58.1393 |
| 0.0278 | 2.1390 | 1000 | 0.0515 | 58.0461 |
| 0.0261 | 3.2086 | 1500 | 0.0538 | 59.1088 |
| 0.0241 | 4.2781 | 2000 | 0.0558 | 60.7190 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.0.2
- Tokenizers 0.20.3
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Model tree for vizsatiz/fauna-v0.7
Base model
openai/whisper-large-v2