---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small.en
tags:
- generated_from_trainer
datasets:
- arlco-calls
metrics:
- wer
model-index:
- name: transcribe-arlco-calls
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: arlco-calls
      type: arlco-calls
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 1.9950487840396096
---

<!-- 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. -->

# transcribe-arlco-calls

This model is a fine-tuned version of [openai/whisper-small.en](https://huggingface.co/openai/whisper-small.en) on the arlco-calls dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0040
- Wer: 1.9950

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.844         | 2.0   | 50   | 0.7820          | 14.4313 |
| 0.3868        | 4.0   | 100  | 0.3769          | 7.6453  |
| 0.1698        | 6.0   | 150  | 0.0941          | 5.4609  |
| 0.0241        | 8.0   | 200  | 0.0248          | 4.9949  |
| 0.0285        | 10.0  | 250  | 0.0102          | 5.1551  |
| 0.007         | 12.0  | 300  | 0.0055          | 2.2426  |
| 0.0027        | 14.0  | 350  | 0.0043          | 1.9659  |
| 0.0031        | 16.0  | 400  | 0.0040          | 1.9950  |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0