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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-64.safetensors +3 -0
  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: 0.4958060228262364
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- name: Wer
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- - type: bleu
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- value: 0.2629057639184852
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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: 0.5099
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- - Wer: 0.4958
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- - Cer: 0.0885
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- - Bleu: 0.2629
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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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- | 11.4061 | 50.0 | 50 | 4.6415 | 1.0007 | 0.9640 | 0.0 |
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- | 1.789 | 100.0 | 100 | 0.3026 | 0.4457 | 0.0734 | 0.3064 |
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- | 0.08 | 150.0 | 150 | 0.3223 | 0.4304 | 0.0711 | 0.3275 |
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- | 0.0473 | 200.0 | 200 | 0.3547 | 0.4426 | 0.0742 | 0.3156 |
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- | 0.0364 | 250.0 | 250 | 0.3786 | 0.4556 | 0.0761 | 0.2972 |
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- | 0.0298 | 300.0 | 300 | 0.4070 | 0.4629 | 0.0800 | 0.2875 |
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- | 0.0279 | 350.0 | 350 | 0.4190 | 0.4688 | 0.0799 | 0.2864 |
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- | 0.0253 | 400.0 | 400 | 0.4353 | 0.4755 | 0.0818 | 0.2757 |
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- | 0.0198 | 450.0 | 450 | 0.4808 | 0.5066 | 0.0887 | 0.2432 |
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- | 0.0216 | 500.0 | 500 | 0.4699 | 0.4780 | 0.0815 | 0.2777 |
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- | 0.0194 | 550.0 | 550 | 0.4745 | 0.4895 | 0.0877 | 0.2643 |
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- | 0.0201 | 600.0 | 600 | 0.5035 | 0.4971 | 0.0881 | 0.2647 |
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- | 0.0153 | 650.0 | 650 | 0.5099 | 0.4958 | 0.0885 | 0.2629 |
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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: 0.4582664894348444
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+ - name: Bleu
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+ type: bleu
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+ value: 0.3001349308741465
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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: 0.4355
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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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  | 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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