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marinone94
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xls-r-300m-sv-robust

Automatic Speech Recognition
Transformers
PyTorch
Swedish
wav2vec2
mozilla-foundation/common_voice_9_0
generated_from_trainer
Eval Results
Inference Endpoints
Model card Files Community
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  ---
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- language:
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- - sv-SE
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  license: cc0-1.0
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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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- - sv
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  - generated_from_trainer
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- - robust-speech-event
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- - model_for_talk
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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-voxrex - Swedish
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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: sv-SE
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- metrics:
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- - name: Test WER
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- type: wer
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- value: 18.89
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- - name: Test CER
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- type: cer
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- value: 6.63
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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: sv
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- metrics:
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- - name: Test WER
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- type: wer
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- value: 30.65
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- - name: Test CER
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- type: cer
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- value: 13.56
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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
@@ -49,10 +14,10 @@ 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 [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SV-SE dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2201
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- - Wer: 0.1778
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  ## Model description
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@@ -71,61 +36,64 @@ More information needed
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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: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 32
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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: 50.0
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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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- | 3.1522 | 1.45 | 500 | 3.1290 | 1.0 |
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- | 2.9576 | 2.91 | 1000 | 2.9633 | 1.0 |
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- | 1.9853 | 4.36 | 1500 | 0.8902 | 0.6104 |
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- | 1.5867 | 5.81 | 2000 | 0.4793 | 0.3664 |
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- | 1.4608 | 7.27 | 2500 | 0.3816 | 0.3095 |
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- | 1.3496 | 8.72 | 3000 | 0.3415 | 0.2783 |
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- | 1.3058 | 10.17 | 3500 | 0.3072 | 0.2519 |
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- | 1.2533 | 11.63 | 4000 | 0.2877 | 0.2381 |
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- | 1.2535 | 13.08 | 4500 | 0.2791 | 0.2320 |
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- | 1.2273 | 14.53 | 5000 | 0.2726 | 0.2282 |
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- | 1.2083 | 15.99 | 5500 | 0.2638 | 0.2212 |
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- | 1.1606 | 17.44 | 6000 | 0.2531 | 0.2174 |
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- | 1.1545 | 18.89 | 6500 | 0.2468 | 0.2109 |
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- | 1.1344 | 20.35 | 7000 | 0.2494 | 0.2050 |
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- | 1.1173 | 21.8 | 7500 | 0.2447 | 0.1980 |
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- | 1.1081 | 23.26 | 8000 | 0.2428 | 0.1998 |
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- | 1.1023 | 24.71 | 8500 | 0.2329 | 0.1951 |
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- | 1.0923 | 26.16 | 9000 | 0.2388 | 0.1962 |
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- | 1.0798 | 27.61 | 9500 | 0.2363 | 0.1944 |
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- | 1.0769 | 29.07 | 10000 | 0.2342 | 0.1913 |
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- | 1.0672 | 30.52 | 10500 | 0.2250 | 0.1875 |
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- | 1.0735 | 31.97 | 11000 | 0.2305 | 0.1874 |
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- | 1.0628 | 33.43 | 11500 | 0.2291 | 0.1851 |
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- | 1.0451 | 34.88 | 12000 | 0.2263 | 0.1856 |
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- | 1.0299 | 36.34 | 12500 | 0.2257 | 0.1834 |
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- | 1.0368 | 37.79 | 13000 | 0.2230 | 0.1808 |
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- | 1.0322 | 39.24 | 13500 | 0.2231 | 0.1833 |
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- | 1.0451 | 40.7 | 14000 | 0.2197 | 0.1817 |
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- | 1.0304 | 42.15 | 14500 | 0.2241 | 0.1813 |
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- | 1.0102 | 43.6 | 15000 | 0.2233 | 0.1795 |
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- | 1.0135 | 45.06 | 15500 | 0.2200 | 0.1794 |
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- | 1.014 | 46.51 | 16000 | 0.2207 | 0.1779 |
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- | 1.0071 | 47.96 | 16500 | 0.2205 | 0.1784 |
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- | 0.9729 | 49.42 | 17000 | 0.2204 | 0.1777 |
 
 
 
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  ### Framework versions
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- - Transformers 4.16.0.dev0
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- - Pytorch 1.10.1+cu102
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- - Datasets 1.17.1.dev0
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  - Tokenizers 0.11.0
 
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  ---
 
 
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  license: cc0-1.0
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  tags:
 
 
 
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  - generated_from_trainer
 
 
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  datasets:
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+ - nst_sv
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  model-index:
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+ - name: ''
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  #
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+ This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the nst_sv dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: inf
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+ - Wer: 1.0
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.00075
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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  - seed: 42
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  - gradient_accumulation_steps: 4
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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: 0.02
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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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+ | 3.4039 | 0.05 | 100 | inf | 1.0 |
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+ | 3.4396 | 0.11 | 200 | inf | 1.0 |
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+ | 3.483 | 0.16 | 300 | inf | 1.0 |
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+ | 3.5014 | 0.21 | 400 | inf | 1.0 |
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+ | 3.331 | 0.27 | 500 | inf | 1.0 |
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+ | 3.4809 | 0.32 | 600 | inf | 1.0 |
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+ | 3.4678 | 0.37 | 700 | inf | 1.0 |
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+ | 3.4596 | 0.43 | 800 | inf | 1.0 |
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+ | 3.4644 | 0.48 | 900 | inf | 1.0 |
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+ | 3.4671 | 0.53 | 1000 | inf | 1.0 |
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+ | 3.6005 | 0.59 | 1100 | inf | 1.0 |
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+ | 3.9182 | 0.64 | 1200 | inf | 1.0 |
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+ | 3.6466 | 0.69 | 1300 | inf | 1.0 |
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+ | 3.6932 | 0.75 | 1400 | inf | 1.0 |
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+ | 3.7939 | 0.8 | 1500 | inf | 1.0 |
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+ | 3.9284 | 0.85 | 1600 | inf | 1.0 |
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+ | 3.7859 | 0.91 | 1700 | inf | 1.0 |
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+ | 3.9363 | 0.96 | 1800 | inf | 1.0 |
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+ | 3.7573 | 1.01 | 1900 | inf | 1.0 |
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+ | 3.7553 | 1.07 | 2000 | inf | 1.0 |
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+ | 3.7606 | 1.12 | 2100 | inf | 1.0 |
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+ | 3.7514 | 1.17 | 2200 | inf | 1.0 |
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+ | 3.7472 | 1.23 | 2300 | inf | 1.0 |
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+ | 3.7478 | 1.28 | 2400 | inf | 1.0 |
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+ | 3.7496 | 1.33 | 2500 | inf | 1.0 |
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+ | 3.7513 | 1.39 | 2600 | inf | 1.0 |
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+ | 3.7497 | 1.44 | 2700 | inf | 1.0 |
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+ | 3.7539 | 1.49 | 2800 | inf | 1.0 |
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+ | 3.7581 | 1.55 | 2900 | inf | 1.0 |
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+ | 3.7572 | 1.6 | 3000 | inf | 1.0 |
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+ | 3.7589 | 1.66 | 3100 | inf | 1.0 |
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+ | 3.7592 | 1.71 | 3200 | inf | 1.0 |
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+ | 3.7531 | 1.76 | 3300 | inf | 1.0 |
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+ | 3.7567 | 1.82 | 3400 | inf | 1.0 |
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+ | 3.7613 | 1.87 | 3500 | inf | 1.0 |
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+ | 3.7516 | 1.92 | 3600 | inf | 1.0 |
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+ | 3.7581 | 1.98 | 3700 | inf | 1.0 |
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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 1.18.3
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  - Tokenizers 0.11.0