Gizachew commited on
Commit
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1 Parent(s): d432275

End of training

Browse files
README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
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  license: apache-2.0
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- base_model: harshit345/xlsr-wav2vec-speech-emotion-recognition
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # ckpts
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- This model is a fine-tuned version of [harshit345/xlsr-wav2vec-speech-emotion-recognition](https://huggingface.co/harshit345/xlsr-wav2vec-speech-emotion-recognition) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2342
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- - Accuracy: 0.9333
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  ## Model description
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@@ -45,15 +45,17 @@ The following hyperparameters were used during training:
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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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- - num_epochs: 5.0
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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 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.4039 | 2.02 | 500 | 0.3198 | 0.8949 |
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- | 0.2195 | 4.04 | 1000 | 0.2363 | 0.9333 |
 
 
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  ### Framework versions
 
1
  ---
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  license: apache-2.0
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+ base_model: facebook/hubert-base-ls960
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  tags:
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  - generated_from_trainer
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  metrics:
 
15
 
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  # ckpts
17
 
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+ This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2499
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+ - Accuracy: 0.9657
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23
  ## Model description
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45
  - 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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+ - num_epochs: 10.0
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  - mixed_precision_training: Native AMP
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51
  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.1792 | 2.02 | 500 | 0.2998 | 0.9313 |
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+ | 0.1097 | 4.04 | 1000 | 0.3281 | 0.9475 |
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+ | 0.0557 | 6.06 | 1500 | 0.2455 | 0.9657 |
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+ | 0.0535 | 8.08 | 2000 | 0.2268 | 0.9657 |
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  ### Framework versions
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