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---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: xls-r-spanish-test
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: es
metrics:
- name: Test WER
type: wer
value: 13.89
- name: Test CER
type: cer
value: 3.85
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: es
metrics:
- name: Test WER
type: wer
value: 37.66
- name: Test CER
type: cer
value: 15.32
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: es
metrics:
- name: Test WER
type: wer
value: 41.17
---
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - ES dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1461
- Wer: 1.0063
## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 2.953 | 0.15 | 1000 | 2.9528 | 1.0 |
| 1.1519 | 0.3 | 2000 | 0.3735 | 1.0357 |
| 1.0278 | 0.45 | 3000 | 0.2529 | 1.0390 |
| 0.9922 | 0.61 | 4000 | 0.2208 | 1.0270 |
| 0.9618 | 0.76 | 5000 | 0.2088 | 1.0294 |
| 0.9364 | 0.91 | 6000 | 0.2019 | 1.0214 |
| 0.9179 | 1.06 | 7000 | 0.1940 | 1.0294 |
| 0.9154 | 1.21 | 8000 | 0.1915 | 1.0290 |
| 0.8985 | 1.36 | 9000 | 0.1837 | 1.0211 |
| 0.9055 | 1.51 | 10000 | 0.1838 | 1.0273 |
| 0.8861 | 1.67 | 11000 | 0.1765 | 1.0139 |
| 0.892 | 1.82 | 12000 | 0.1723 | 1.0188 |
| 0.8778 | 1.97 | 13000 | 0.1735 | 1.0092 |
| 0.8645 | 2.12 | 14000 | 0.1707 | 1.0106 |
| 0.8595 | 2.27 | 15000 | 0.1713 | 1.0186 |
| 0.8392 | 2.42 | 16000 | 0.1686 | 1.0053 |
| 0.8436 | 2.57 | 17000 | 0.1653 | 1.0096 |
| 0.8405 | 2.73 | 18000 | 0.1689 | 1.0077 |
| 0.8382 | 2.88 | 19000 | 0.1645 | 1.0114 |
| 0.8247 | 3.03 | 20000 | 0.1647 | 1.0078 |
| 0.8219 | 3.18 | 21000 | 0.1611 | 1.0026 |
| 0.8024 | 3.33 | 22000 | 0.1580 | 1.0062 |
| 0.8087 | 3.48 | 23000 | 0.1578 | 1.0038 |
| 0.8097 | 3.63 | 24000 | 0.1556 | 1.0057 |
| 0.8094 | 3.79 | 25000 | 0.1552 | 1.0035 |
| 0.7836 | 3.94 | 26000 | 0.1516 | 1.0052 |
| 0.8042 | 4.09 | 27000 | 0.1515 | 1.0054 |
| 0.7925 | 4.24 | 28000 | 0.1499 | 1.0031 |
| 0.7855 | 4.39 | 29000 | 0.1490 | 1.0041 |
| 0.7814 | 4.54 | 30000 | 0.1482 | 1.0068 |
| 0.7859 | 4.69 | 31000 | 0.1460 | 1.0066 |
| 0.7819 | 4.85 | 32000 | 0.1464 | 1.0062 |
| 0.7784 | 5.0 | 33000 | 0.1460 | 1.0063 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3.dev0
- Tokenizers 0.11.0
|