metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
model-index:
- name: uaspeech-large-finetune-long-evals-30-11-11AM
results: []
uaspeech-large-finetune-long-evals-30-11-11AM
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3481
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2252 | 0.2070 | 500 | 0.3504 |
| 0.1217 | 0.4139 | 1000 | 0.3028 |
| 0.071 | 0.6209 | 1500 | 0.3409 |
| 0.0581 | 0.8278 | 2000 | 0.3390 |
| 0.0279 | 1.0348 | 2500 | 0.3261 |
| 0.0132 | 1.2417 | 3000 | 0.3258 |
| 0.006 | 1.4487 | 3500 | 0.3280 |
| 0.0077 | 1.6556 | 4000 | 0.3553 |
| 0.0094 | 1.8626 | 4500 | 0.3516 |
| 0.0043 | 2.0695 | 5000 | 0.3481 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3