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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- verba_lex_voice
metrics:
- wer
model-index:
- name: verbalex-hi
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: verba_lex_voice
type: verba_lex_voice
config: hi
split: test
args: hi
metrics:
- type: wer
value: 1.6019256308100929
name: Wer
---
<!-- 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. -->
# verbalex-hi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the verba_lex_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0554
- Wer: 1.6019
## 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0011 | 5.0505 | 1000 | 0.0504 | 1.7762 |
| 0.0001 | 10.1010 | 2000 | 0.0529 | 1.6268 |
| 0.0001 | 15.1515 | 3000 | 0.0541 | 1.6434 |
| 0.0001 | 20.2020 | 4000 | 0.0550 | 1.6102 |
| 0.0 | 25.2525 | 5000 | 0.0554 | 1.6019 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.19.1
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