|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- luigisaetta/atco2_atcosim |
|
metrics: |
|
- wer |
|
base_model: openai/whisper-medium |
|
model-index: |
|
- name: whisper-atcosim |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# whisper-atcosim |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the |
|
atco2_atcosim dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0628 |
|
- Wer: 0.0369 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 2 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 32 |
|
- total_eval_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 100 |
|
- training_steps: 200 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.5702 | 0.2 | 50 | 0.2557 | 0.1007 | |
|
| 0.1181 | 0.39 | 100 | 0.1144 | 0.0775 | |
|
| 0.1073 | 0.59 | 150 | 0.0740 | 0.0529 | |
|
| 0.0747 | 0.79 | 200 | 0.0628 | 0.0369 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.29.0 |
|
- Pytorch 2.0.0+cu117 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.11.0 |
