122 lines
3.5 KiB
Markdown
122 lines
3.5 KiB
Markdown
---
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language:
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- fr
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_7_0
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- generated_from_trainer
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- robust-speech-event
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- hf-asr-leaderboard
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datasets:
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- mozilla-foundation/common_voice_7_0
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model-index:
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- name: XLS-R-300M - French
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Common Voice 7
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type: mozilla-foundation/common_voice_7_0
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args: fr
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metrics:
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- name: Test WER
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type: wer
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value: 24.56
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- name: Test CER
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type: cer
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value: 7.3
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Robust Speech Event - Dev Data
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type: speech-recognition-community-v2/dev_data
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args: fr
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metrics:
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- name: Test WER
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type: wer
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value: 63.62
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- name: Test CER
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type: cer
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value: 17.2
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Robust Speech Event - Test Data
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type: speech-recognition-community-v2/eval_data
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args: fr
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metrics:
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- name: Test WER
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type: wer
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value: 66.45
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---
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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## Model description
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FR dataset.
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 7.5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 2000
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- num_epochs: 2.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 3.495 | 0.16 | 500 | 3.3883 | 1.0 |
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| 2.9095 | 0.32 | 1000 | 2.9152 | 1.0000 |
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| 1.8434 | 0.49 | 1500 | 1.0473 | 0.7446 |
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| 1.4298 | 0.65 | 2000 | 0.5729 | 0.5130 |
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| 1.1937 | 0.81 | 2500 | 0.3795 | 0.3450 |
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| 1.1248 | 0.97 | 3000 | 0.3321 | 0.3052 |
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| 1.0835 | 1.13 | 3500 | 0.3038 | 0.2805 |
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| 1.0479 | 1.3 | 4000 | 0.2910 | 0.2689 |
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| 1.0413 | 1.46 | 4500 | 0.2798 | 0.2593 |
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| 1.014 | 1.62 | 5000 | 0.2727 | 0.2512 |
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| 1.004 | 1.78 | 5500 | 0.2646 | 0.2471 |
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| 0.9949 | 1.94 | 6000 | 0.2619 | 0.2457 |
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It achieves the best result on STEP 6000 on the validation set:
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- Loss: 0.2619
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- Wer: 0.2457
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2.dev0
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- Tokenizers 0.11.0
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### Evaluation Commands
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1. To evaluate on `mozilla-foundation/common_voice_7` with split `test`
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```bash
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python eval.py --model_id Plim/xls-r-300m-fr --dataset mozilla-foundation/common_voice_7_0 --config fr --split test
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```
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2. To evaluate on `speech-recognition-community-v2/dev_data`
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```bash
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python eval.py --model_id Plim/xls-r-300m-fr --dataset speech-recognition-community-v2/dev_data --config fr --split validation --chunk_length_s 5.0 --stride_length_s 1.0
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```
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