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EzraWilliam
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wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod8

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
EzraWilliam commited on
Commit
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1 Parent(s): 2b8aa70

End of training

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Files changed (3) hide show
  1. README.md +21 -15
  2. model.safetensors +1 -1
  3. runs/Mar23_13-55-36_1deffeda88bf/events.out.tfevents.1711202170.1deffeda88bf.1671.0 +2 -2
README.md CHANGED
@@ -1,8 +1,8 @@
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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- base_model: facebook/wav2vec2-large-xlsr-53
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  datasets:
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  - xtreme_s
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  metrics:
@@ -11,8 +11,8 @@ model-index:
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  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod8
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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: xtreme_s
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  type: xtreme_s
@@ -20,9 +20,9 @@ model-index:
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  split: test
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  args: fleurs.id_id
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  metrics:
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- - type: wer
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- value: 0.42321508756174225
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- name: Wer
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8564
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- - Wer: 0.4232
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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- - train_batch_size: 16
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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: 64
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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: 600
@@ -68,16 +68,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:------:|
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- | 4.801 | 30.77 | 300 | 2.8357 | 1.0 |
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- | 1.041 | 61.54 | 600 | 0.8673 | 0.5433 |
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- | 0.1141 | 92.31 | 900 | 0.8976 | 0.4801 |
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- | 0.0568 | 123.08 | 1200 | 0.8556 | 0.4427 |
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- | 0.035 | 153.85 | 1500 | 0.8564 | 0.4232 |
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.39.0
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  ---
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  license: apache-2.0
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+ base_model: facebook/wav2vec2-large-xlsr-53
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  tags:
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  - generated_from_trainer
 
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  datasets:
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  - xtreme_s
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  metrics:
 
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  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod8
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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: xtreme_s
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  type: xtreme_s
 
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  split: test
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  args: fleurs.id_id
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.42037120191588084
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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/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9283
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+ - Wer: 0.4204
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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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: 600
 
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:------:|
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+ | 4.7974 | 15.58 | 300 | 2.8438 | 1.0 |
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+ | 1.0661 | 31.17 | 600 | 0.7520 | 0.5781 |
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+ | 0.1697 | 46.75 | 900 | 0.8342 | 0.5181 |
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+ | 0.1081 | 62.34 | 1200 | 0.8508 | 0.5010 |
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+ | 0.0833 | 77.92 | 1500 | 0.9216 | 0.5014 |
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+ | 0.0616 | 93.51 | 1800 | 0.9659 | 0.4859 |
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+ | 0.0463 | 109.09 | 2100 | 0.9606 | 0.4646 |
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+ | 0.0356 | 124.68 | 2400 | 0.9255 | 0.4578 |
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+ | 0.0291 | 140.26 | 2700 | 0.9889 | 0.4503 |
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+ | 0.0218 | 155.84 | 3000 | 0.9336 | 0.4371 |
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+ | 0.0182 | 171.43 | 3300 | 0.9283 | 0.4204 |
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  ### Framework versions
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+ - Transformers 4.39.1
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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