transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-te
  results: []
---

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# whisper-small-te

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4501
- Wer: 95.6522

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1715        | 25.0  | 100  | 1.2209          | 99.1304 |
| 0.0021        | 50.0  | 200  | 1.2032          | 99.1304 |
| 0.0001        | 75.0  | 300  | 1.2996          | 96.5217 |
| 0.0001        | 100.0 | 400  | 1.3443          | 97.3913 |
| 0.0001        | 125.0 | 500  | 1.3752          | 97.3913 |
| 0.0001        | 150.0 | 600  | 1.3996          | 96.5217 |
| 0.0001        | 175.0 | 700  | 1.4199          | 96.5217 |
| 0.0001        | 200.0 | 800  | 1.4359          | 95.6522 |
| 0.0001        | 225.0 | 900  | 1.4458          | 95.6522 |
| 0.0001        | 250.0 | 1000 | 1.4501          | 95.6522 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
