Fauna-v3.6 - Rootflo
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1129
- Bleu: 19.6035
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: 2e-06
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 768
- 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: 100
- training_steps: 0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 0.3935 | 0.9961 | 129 | 0.1285 | 16.5443 |
| 0.2695 | 2.0 | 259 | 0.1173 | 18.5659 |
| 0.2469 | 2.9961 | 388 | 0.1135 | 11.4429 |
| 0.2285 | 3.9846 | 516 | 0.1129 | 19.6035 |
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-v3.6
Base model
openai/whisper-large-v3