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ndeclarke
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wav2vec2-mms-1b-CV17.0-training_set_variations

Automatic Speech Recognition
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wav2vec2
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End of training

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  1. README.md +28 -28
  2. adapter.tam-128.safetensors +1 -1
  3. model.safetensors +1 -1
README.md CHANGED
@@ -1,20 +1,20 @@
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  ---
 
 
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  base_model: facebook/mms-1b-all
 
 
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  datasets:
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  - common_voice_17_0
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- library_name: transformers
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- license: cc-by-nc-4.0
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  metrics:
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  - wer
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  - bleu
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- tags:
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- - generated_from_trainer
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  model-index:
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  - name: wav2vec2-mms-1b-CV17.0-training_set_variations
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  results:
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  - task:
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- type: automatic-speech-recognition
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  name: Automatic Speech Recognition
 
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  dataset:
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  name: common_voice_17_0
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  type: common_voice_17_0
@@ -22,12 +22,12 @@ model-index:
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  split: validation
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  args: ta
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  metrics:
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- - type: wer
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- value: 0.4582664894348444
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- name: Wer
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- - type: bleu
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- value: 0.3001349308741465
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- name: Bleu
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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
@@ -37,10 +37,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4355
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- - Wer: 0.4583
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- - Cer: 0.0787
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- - Bleu: 0.3001
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  ## Model description
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@@ -75,19 +75,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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- | 12.8763 | 25.0 | 50 | 4.9690 | 1.0000 | 0.9319 | 0.0 |
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- | 2.2038 | 50.0 | 100 | 0.3040 | 0.4239 | 0.0696 | 0.3337 |
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- | 0.1153 | 75.0 | 150 | 0.2911 | 0.4134 | 0.0685 | 0.3474 |
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- | 0.0557 | 100.0 | 200 | 0.3344 | 0.4333 | 0.0718 | 0.3271 |
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- | 0.0448 | 125.0 | 250 | 0.3486 | 0.4403 | 0.0743 | 0.3213 |
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- | 0.0382 | 150.0 | 300 | 0.3938 | 0.4499 | 0.0762 | 0.3102 |
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- | 0.0364 | 175.0 | 350 | 0.3927 | 0.4525 | 0.0778 | 0.3045 |
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- | 0.0286 | 200.0 | 400 | 0.3883 | 0.4417 | 0.0744 | 0.3173 |
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- | 0.0293 | 225.0 | 450 | 0.4235 | 0.4656 | 0.0794 | 0.2913 |
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- | 0.0296 | 250.0 | 500 | 0.4432 | 0.4710 | 0.0817 | 0.2771 |
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- | 0.0302 | 275.0 | 550 | 0.4266 | 0.4524 | 0.0765 | 0.3016 |
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- | 0.0252 | 300.0 | 600 | 0.4376 | 0.4717 | 0.0815 | 0.2793 |
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- | 0.0216 | 325.0 | 650 | 0.4355 | 0.4583 | 0.0787 | 0.3001 |
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  ### Framework versions
 
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  ---
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+ library_name: transformers
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+ license: cc-by-nc-4.0
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  base_model: facebook/mms-1b-all
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+ tags:
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+ - generated_from_trainer
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  datasets:
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  - common_voice_17_0
 
 
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  metrics:
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  - wer
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  - bleu
 
 
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  model-index:
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  - name: wav2vec2-mms-1b-CV17.0-training_set_variations
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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_17_0
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  type: common_voice_17_0
 
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  split: validation
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  args: ta
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.45588302699729566
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+ - name: Bleu
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+ type: bleu
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+ value: 0.30120570288375
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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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  This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4242
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+ - Wer: 0.4559
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+ - Cer: 0.0764
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+ - Bleu: 0.3012
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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+ | 13.1596 | 12.5 | 50 | 6.8694 | 1.0 | 0.9625 | 0.0 |
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+ | 3.2131 | 25.0 | 100 | 0.4085 | 0.4707 | 0.0784 | 0.2830 |
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+ | 0.1719 | 37.5 | 150 | 0.2583 | 0.3920 | 0.0650 | 0.3818 |
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+ | 0.0962 | 50.0 | 200 | 0.2869 | 0.4118 | 0.0682 | 0.3547 |
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+ | 0.0648 | 62.5 | 250 | 0.3209 | 0.4213 | 0.0696 | 0.3435 |
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+ | 0.0613 | 75.0 | 300 | 0.3404 | 0.4454 | 0.0742 | 0.3200 |
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+ | 0.0515 | 87.5 | 350 | 0.3744 | 0.4385 | 0.0734 | 0.3289 |
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+ | 0.0426 | 100.0 | 400 | 0.3835 | 0.4479 | 0.0748 | 0.3078 |
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+ | 0.0384 | 112.5 | 450 | 0.3776 | 0.4432 | 0.0746 | 0.3243 |
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+ | 0.0363 | 125.0 | 500 | 0.4053 | 0.4371 | 0.0732 | 0.3251 |
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+ | 0.0385 | 137.5 | 550 | 0.4225 | 0.4520 | 0.0772 | 0.3115 |
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+ | 0.0343 | 150.0 | 600 | 0.4295 | 0.4463 | 0.0758 | 0.3167 |
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+ | 0.0371 | 162.5 | 650 | 0.4242 | 0.4559 | 0.0764 | 0.3012 |
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  ### Framework versions
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