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infinitejoy
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wav2vec2-large-xls-r-300m-hindi

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hindi
wav2vec2
generated_from_trainer
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_7_0
robust-speech-event
Eval Results
Inference Endpoints
Model card Files Metrics Community
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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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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 common_voice dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 5.8345
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- - Wer: 1.0592
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  ## Model description
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@@ -45,25 +45,36 @@ The following hyperparameters were used during training:
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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: 500
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- - num_epochs: 400
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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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- | 6.0837 | 57.14 | 400 | 3.3819 | 1.0081 |
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- | 0.2254 | 114.29 | 800 | 4.4935 | 1.0255 |
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- | 0.061 | 171.43 | 1200 | 5.1464 | 1.0870 |
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- | 0.0282 | 228.57 | 1600 | 5.6430 | 1.0789 |
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- | 0.0144 | 285.71 | 2000 | 5.7916 | 1.0940 |
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- | 0.0077 | 342.86 | 2400 | 5.8701 | 1.0580 |
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- | 0.0041 | 400.0 | 2800 | 5.8345 | 1.0592 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.11.3
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  - Pytorch 1.10.0+cu113
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- - Datasets 1.13.3
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  - Tokenizers 0.10.3
 
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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 common_voice dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.6718
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+ - Wer: 0.7103
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  ## Model description
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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: 500
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+ - num_epochs: 50
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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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+ | 5.5682 | 2.72 | 400 | 2.1019 | 0.9188 |
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+ | 0.6506 | 5.44 | 800 | 1.9496 | 0.8048 |
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+ | 0.3249 | 8.16 | 1200 | 1.8901 | 0.7515 |
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+ | 0.222 | 10.88 | 1600 | 1.7736 | 0.7115 |
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+ | 0.171 | 13.6 | 2000 | 2.1061 | 0.7507 |
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+ | 0.1428 | 16.33 | 2400 | 2.2476 | 0.7412 |
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+ | 0.1235 | 19.05 | 2800 | 2.3527 | 0.7554 |
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+ | 0.1076 | 21.77 | 3200 | 2.2145 | 0.7404 |
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+ | 0.0982 | 24.49 | 3600 | 2.3603 | 0.7327 |
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+ | 0.0842 | 27.21 | 4000 | 2.4086 | 0.7465 |
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+ | 0.0732 | 29.93 | 4400 | 2.4182 | 0.7259 |
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+ | 0.0672 | 32.65 | 4800 | 2.5249 | 0.7315 |
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+ | 0.0601 | 35.37 | 5200 | 2.5355 | 0.7207 |
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+ | 0.0534 | 38.09 | 5600 | 2.5170 | 0.7191 |
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+ | 0.0477 | 40.81 | 6000 | 2.6001 | 0.7064 |
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+ | 0.0435 | 43.54 | 6400 | 2.7135 | 0.7142 |
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+ | 0.0374 | 46.26 | 6800 | 2.6552 | 0.7127 |
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+ | 0.0348 | 48.98 | 7200 | 2.6718 | 0.7103 |
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  ### Framework versions
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+ - Transformers 4.16.0.dev0
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  - Pytorch 1.10.0+cu113
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+ - Datasets 1.17.1.dev0
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  - Tokenizers 0.10.3