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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-atcosim3
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-atcosim3
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium)
on the [atco2_atcosim](https://huggingface.co/datasets/luigisaetta/atco2_atcosim)
dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0476
- Wer: 0.0198
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
The model has been trained on the [atco2_atcosim](https://huggingface.co/datasets/luigisaetta/atco2_atcosim)
dataset.
## 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: 150
- training_steps: 600
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8218 | 0.2 | 50 | 0.3785 | 0.1451 |
| 0.1429 | 0.39 | 100 | 0.1213 | 0.0714 |
| 0.1155 | 0.59 | 150 | 0.0807 | 0.0517 |
| 0.0764 | 0.79 | 200 | 0.0652 | 0.0272 |
| 0.0724 | 0.98 | 250 | 0.0607 | 0.0393 |
| 0.0357 | 1.18 | 300 | 0.0569 | 0.0242 |
| 0.03 | 1.38 | 350 | 0.0553 | 0.0243 |
| 0.0325 | 1.57 | 400 | 0.0556 | 0.0228 |
| 0.03 | 1.77 | 450 | 0.0501 | 0.0242 |
| 0.0232 | 1.97 | 500 | 0.0485 | 0.0205 |
| 0.0143 | 2.16 | 550 | 0.0480 | 0.0194 |
| 0.0105 | 2.36 | 600 | 0.0476 | 0.0198 |
### Framework versions
- Transformers 4.29.0
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.11.0
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