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End of training

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README.md CHANGED
@@ -15,9 +15,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # Osiris_asr_model
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- This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 6.1959
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  - Wer: 1.0
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  ## Model description
@@ -38,23 +38,41 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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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: 5
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- - training_steps: 100
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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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- | 14.2416 | 25.0 | 50 | 11.0457 | 1.0 |
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- | 7.9736 | 50.0 | 100 | 6.1959 | 1.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  # Osiris_asr_model
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0600
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  - Wer: 1.0
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  ## Model description
 
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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+ - train_batch_size: 10
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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: 20
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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: 50
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+ - training_steps: 1000
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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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+ | 45.8209 | 50.0 | 50 | 21.0347 | 1.0182 |
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+ | 10.2898 | 100.0 | 100 | 5.1552 | 1.0 |
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+ | 5.7188 | 150.0 | 150 | 4.9140 | 1.0 |
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+ | 5.3358 | 200.0 | 200 | 4.7650 | 1.0 |
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+ | 5.1381 | 250.0 | 250 | 4.6797 | 1.0 |
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+ | 4.9841 | 300.0 | 300 | 4.6168 | 1.0 |
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+ | 4.9255 | 350.0 | 350 | 4.5741 | 1.0 |
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+ | 4.8353 | 400.0 | 400 | 4.5321 | 1.0 |
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+ | 4.7704 | 450.0 | 450 | 4.5100 | 1.0 |
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+ | 4.6257 | 500.0 | 500 | 3.9382 | 1.0 |
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+ | 3.8106 | 550.0 | 550 | 3.3939 | 1.0 |
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+ | 3.5095 | 600.0 | 600 | 3.2887 | 1.0 |
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+ | 3.3716 | 650.0 | 650 | 3.1967 | 1.0 |
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+ | 3.3025 | 700.0 | 700 | 3.1539 | 1.0 |
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+ | 3.2532 | 750.0 | 750 | 3.1477 | 1.0 |
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+ | 3.2086 | 800.0 | 800 | 3.0984 | 1.0 |
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+ | 3.1889 | 850.0 | 850 | 3.0857 | 1.0 |
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+ | 3.162 | 900.0 | 900 | 3.0819 | 1.0 |
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+ | 3.1411 | 950.0 | 950 | 3.0610 | 1.0 |
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+ | 3.1397 | 1000.0 | 1000 | 3.0600 | 1.0 |
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  ### Framework versions
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