whisper-small-ml / README.md
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---
library_name: transformers
language:
- ml
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- asr-malayalam/spring_ml_conversation
metrics:
- wer
model-index:
- name: Whisper Small ML chan73
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Spring ML
type: asr-malayalam/spring_ml_conversation
metrics:
- name: Wer
type: wer
value: 60.68040364976736
---
<!-- 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 Small ML chan73
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Spring ML dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3561
- Wer Ortho: 91.3568
- Wer: 60.6804
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.2293 | 3.8502 | 500 | 0.3561 | 91.3568 | 60.6804 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1