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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- arrow
metrics:
- wer
model-index:
- name: dialect
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: arrow
type: arrow
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 0.0
---
<!-- 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. -->
# dialect
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 0.0
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.0444 | 0.2404 | 1000 | 0.0239 | 3.75 |
| 0.0115 | 0.4808 | 2000 | 0.0157 | 1.5385 |
| 0.0047 | 0.7212 | 3000 | 0.0844 | 4.4231 |
| 0.0153 | 0.9615 | 4000 | 0.0050 | 0.6731 |
| 0.0192 | 1.2019 | 5000 | 0.0017 | 0.1923 |
| 0.0 | 1.4423 | 6000 | 0.0075 | 0.8654 |
| 0.0 | 1.6827 | 7000 | 0.0002 | 0.0962 |
| 0.0274 | 1.9231 | 8000 | 0.0195 | 2.2115 |
| 0.0 | 2.1635 | 9000 | 0.0179 | 1.0577 |
| 0.0402 | 2.4038 | 10000 | 0.0020 | 0.0962 |
| 0.0161 | 2.6442 | 11000 | 0.0050 | 0.3846 |
| 0.0009 | 2.8846 | 12000 | 0.0048 | 0.2885 |
| 0.0 | 3.125 | 13000 | 0.0031 | 0.1923 |
| 0.0 | 3.3654 | 14000 | 0.0029 | 0.1923 |
| 0.0 | 3.6058 | 15000 | 0.0029 | 0.1923 |
| 0.0 | 3.8462 | 16000 | 0.0043 | 0.1923 |
| 0.0 | 4.0865 | 17000 | 0.0008 | 0.0962 |
| 0.0 | 4.3269 | 18000 | 0.0000 | 0.0 |
| 0.0 | 4.5673 | 19000 | 0.0000 | 0.0 |
| 0.0 | 4.8077 | 20000 | 0.0001 | 0.0 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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