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--- |
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language: |
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- mr |
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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_9_0 |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_9_0 |
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metrics: |
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- wer |
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model-index: |
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- name: XLS-R-300M - Marathi |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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type: mozilla-foundation/common_voice_9_0 |
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name: Common Voice 9 |
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args: mr |
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metrics: |
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- type: wer |
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value: 23.841 |
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name: Test WER |
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- name: Test CER |
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type: cer |
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value: 5.522 |
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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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# |
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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_9_0 - MR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3642 |
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- Wer: 0.4190 |
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- Cer: 0.0946 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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_ratio: 0.1 |
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- training_steps: 6124 |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| 3.5184 | 12.9 | 400 | 3.4210 | 1.0 | 1.0 | |
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| 2.3797 | 25.81 | 800 | 1.1068 | 0.8389 | 0.2584 | |
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| 1.5022 | 38.71 | 1200 | 0.5278 | 0.6280 | 0.1517 | |
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| 1.3181 | 51.61 | 1600 | 0.4254 | 0.5587 | 0.1297 | |
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| 1.2037 | 64.52 | 2000 | 0.3836 | 0.5143 | 0.1176 | |
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| 1.1245 | 77.42 | 2400 | 0.3643 | 0.4871 | 0.1111 | |
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| 1.0582 | 90.32 | 2800 | 0.3562 | 0.4676 | 0.1062 | |
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| 1.0027 | 103.23 | 3200 | 0.3530 | 0.4625 | 0.1058 | |
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| 0.9382 | 116.13 | 3600 | 0.3388 | 0.4442 | 0.1002 | |
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| 0.8915 | 129.03 | 4000 | 0.3430 | 0.4427 | 0.1000 | |
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| 0.853 | 141.94 | 4400 | 0.3536 | 0.4375 | 0.1000 | |
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| 0.8127 | 154.84 | 4800 | 0.3511 | 0.4344 | 0.0986 | |
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| 0.7861 | 167.74 | 5200 | 0.3595 | 0.4372 | 0.0993 | |
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| 0.7619 | 180.65 | 5600 | 0.3628 | 0.4316 | 0.0985 | |
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| 0.7537 | 193.55 | 6000 | 0.3633 | 0.4174 | 0.0943 | |
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### Framework versions |
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- Transformers 4.19.0.dev0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.1.1.dev0 |
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- Tokenizers 0.12.1 |
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