transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:google/fleurs base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Breeze DSW Telugu - base
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs te_in
      type: google/fleurs
      config: te_in
      split: test
      args: te_in
    metrics:
    - name: Wer
      type: wer
      value: 37.45436058603319
---

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# Breeze DSW Telugu - base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs te_in dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3372
- Wer: 37.4544

## 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: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2937        | 2.03  | 200  | 0.3237          | 42.5614 |
| 0.1611        | 5.02  | 400  | 0.2756          | 38.9148 |
| 0.0889        | 8.01  | 600  | 0.2930          | 38.1106 |
| 0.0456        | 11.0  | 800  | 0.3372          | 37.4544 |
| 0.0229        | 13.03 | 1000 | 0.3982          | 37.9258 |
| 0.0103        | 16.02 | 1200 | 0.4473          | 38.2678 |
| 0.0042        | 19.02 | 1400 | 0.4836          | 37.8980 |
| 0.0025        | 22.01 | 1600 | 0.5083          | 37.7317 |
| 0.002         | 24.04 | 1800 | 0.5220          | 37.8010 |
| 0.0018        | 27.03 | 2000 | 0.5269          | 37.9027 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
