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dongahn
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my_awesome_asr_mind_model

Automatic Speech Recognition
Transformers
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Safetensors
wav2vec2
Generated from Trainer
Eval Results
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dongahn commited on
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1 Parent(s): 28c7eb5

Training in progress, step 1000

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Files changed (3) hide show
  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.6638297872340425
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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-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4341
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- - Wer: 0.6638
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  ## Model description
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@@ -53,11 +53,11 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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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: 2
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- - total_train_batch_size: 16
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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
@@ -68,13 +68,13 @@ 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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- | 0.0999 | 200.0 | 1000 | 1.9330 | 0.6681 |
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- | 0.018 | 400.0 | 2000 | 2.4341 | 0.6638 |
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  ### Framework versions
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  - Transformers 4.42.3
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- - Pytorch 2.3.1+cu121
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.7633333333333333
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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-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0211
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+ - Wer: 0.7633
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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+ - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
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  - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.1841 | 100.0 | 1000 | 2.4919 | 0.74 |
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+ | 0.0295 | 200.0 | 2000 | 3.0211 | 0.7633 |
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  ### Framework versions
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  - Transformers 4.42.3
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+ - Pytorch 2.3.1
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
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