transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer es dataset:Marianoleiras/voxpopuli_es-ja base_model:openai/whisper-small base_model:finetune:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
base_model: openai/whisper-small
datasets:
- Marianoleiras/voxpopuli_es-ja
language:
- es
library_name: transformers
license: apache-2.0
metrics:
- wer
pipeline_tag: automatic-speech-recognition
tags:
- generated_from_trainer
model-index:
- name: whisper-small-es
  results: []
---

<!-- 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-es

## Model Overview
This model was developed as part of a workshop organized by Yasmin Moslem, focusing on **speech-to-text pipelines**.
The workshop's primary goal was to enable accurate transcription and translation of spoken source languages into written target languages while learning about end-to-end and cascaded approaches in the process. 

This model is a fine-tuned version of [OpenAI's Whisper-Small](https://huggingface.co/openai/whisper-small) trained on the [voxpopuli_es-ja](https://huggingface.co/datasets/Marianoleiras/voxpopuli_es-ja) dataset for **Spanish Automatic Speech Recognition (ASR)**. 

The model achieves performance metrics on the provided dataset:

**Evaluation Set:**
- Loss: **0.2071**
- WER: **9.5996**

**Test Set:**
- WER: **10.1251**

(Baseline evaluation on test set: 36.7506)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.2207        | 0.8013 | 250  | 0.2146          | 9.9606 |
| 0.1558        | 1.6026 | 500  | 0.2071          | 9.5996 |
| 0.1373        | 2.4038 | 750  | 0.2067          | 9.6622 |
| 0.1133        | 3.2051 | 1000 | 0.2055          | 9.6438 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3


## Linked Models

- **[Whisper-Small-es-ja](https://huggingface.co/Marianoleiras/whisper-small-es-ja)**: An end-to-end model trained on this dataset.
- **[NLLB-200-Distilled-es-ja](https://huggingface.co/Marianoleiras/nllb-200-distilled-es-ja)**: The MT model of the cascaded approach built using this dataset.

# Model Card Contact

Mariano González (marianoleiras@hotmail.com)
