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---
language:
- pt
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_7_0
- pt
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: wav2vec2_base_10k_8khz_pt_cv7_2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: pt
metrics:
- name: Test WER
type: wer
value: 36.9
- name: Test CER
type: cer
value: 14.82
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: sv
metrics:
- name: Test WER
type: wer
value: 40.53
- name: Test CER
type: cer
value: 16.95
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: pt
metrics:
- name: Test WER
type: wer
value: 37.15
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: pt
metrics:
- name: Test WER
type: wer
value: 38.95
---
<!-- 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. -->
# wav2vec2_base_10k_8khz_pt_cv7_2
This model is a fine-tuned version of [lgris/seasr_2022_base_10k_8khz_pt](https://huggingface.co/lgris/seasr_2022_base_10k_8khz_pt) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 76.3426
- Wer: 0.1979
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 189.1362 | 0.65 | 500 | 80.6347 | 0.2139 |
| 174.2587 | 1.3 | 1000 | 80.2062 | 0.2116 |
| 164.676 | 1.95 | 1500 | 78.2161 | 0.2073 |
| 176.5856 | 2.6 | 2000 | 78.8920 | 0.2074 |
| 164.3583 | 3.25 | 2500 | 77.2865 | 0.2066 |
| 161.414 | 3.9 | 3000 | 77.8888 | 0.2048 |
| 158.283 | 4.55 | 3500 | 77.3472 | 0.2033 |
| 159.2265 | 5.19 | 4000 | 79.0953 | 0.2036 |
| 156.3967 | 5.84 | 4500 | 76.6855 | 0.2029 |
| 154.2743 | 6.49 | 5000 | 77.7785 | 0.2015 |
| 156.6497 | 7.14 | 5500 | 77.1220 | 0.2033 |
| 157.3038 | 7.79 | 6000 | 76.2926 | 0.2027 |
| 162.8151 | 8.44 | 6500 | 76.7602 | 0.2013 |
| 151.8613 | 9.09 | 7000 | 77.4777 | 0.2011 |
| 153.0225 | 9.74 | 7500 | 76.5206 | 0.2001 |
| 157.52 | 10.39 | 8000 | 76.1061 | 0.2006 |
| 145.0592 | 11.04 | 8500 | 76.7855 | 0.1992 |
| 150.0066 | 11.69 | 9000 | 76.0058 | 0.1988 |
| 146.8128 | 12.34 | 9500 | 76.2853 | 0.1987 |
| 146.9148 | 12.99 | 10000 | 76.3426 | 0.1979 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
|