---
library_name: transformers
license: apache-2.0
base_model: KJnr/finetuned-whisper-small-V1.0.0
tags:
- generated_from_trainer
datasets:
- generator
metrics:
- wer
model-index:
- name: whisper-small-mult-2xt-continued
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: generator
      type: generator
      config: default
      split: None
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 53.503161450843436
---

<!-- 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-mult-2xt-continued

This model is a fine-tuned version of [KJnr/finetuned-whisper-small-V1.0.0](https://huggingface.co/KJnr/finetuned-whisper-small-V1.0.0) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4920
- Wer: 53.5032

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- 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_ratio: 0.05
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.268         | 0.3333 | 1000 | 0.5192          | 69.2031 |
| 0.2296        | 0.6667 | 2000 | 0.5010          | 49.9377 |
| 0.2441        | 1.0    | 3000 | 0.4920          | 53.5032 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0