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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
base_model: juancopi81/whisper-medium-es-train-valid
model-index:
- name: juancopi81/whisper-medium-es-train-valid
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: es
split: test
args: es
metrics:
- type: wer
value: 6.15482563276337
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. -->
# juancopi81/whisper-medium-es-train-valid
This model is a fine-tuned version of [juancopi81/whisper-medium-es-train-valid](https://huggingface.co/juancopi81/whisper-medium-es-train-valid) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2227
- Wer: 6.1548
Using the script provided in the Whisper Sprint (Dec. 2022) the models achieves these results on the evaluation sets (WER):
- google/fleurs: 6.94
- mozilla-foundation/common_voice_11_0: XXXX
## 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: 32
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0539 | 1.01 | 1000 | 0.2100 | 6.4465 |
| 0.0211 | 2.01 | 2000 | 0.2286 | 6.5082 |
| 0.0088 | 3.02 | 3000 | 0.2418 | 6.3848 |
| 0.0205 | 4.02 | 4000 | 0.2288 | 6.6603 |
| 0.1031 | 5.03 | 5000 | 0.2227 | 6.1548 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|