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Krithika-p
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my_awesome_emotions_model

Audio Classification
Transformers
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wav2vec2
Generated from Trainer
Eval Results
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  1. README.md +76 -2
  2. model.safetensors +1 -1
  3. runs/Dec13_00-44-20_8d432ef5f737/events.out.tfevents.1702428266.8d432ef5f737.332.0 +2 -2
  4. runs/Dec13_00-44-20_8d432ef5f737/events.out.tfevents.1702431456.8d432ef5f737.332.1 +3 -0
README.md CHANGED
@@ -3,9 +3,26 @@ license: apache-2.0
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  base_model: facebook/wav2vec2-base
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  tags:
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  - generated_from_trainer
 
 
 
 
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  model-index:
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  - name: my_awesome_emotions_model
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -13,7 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # my_awesome_emotions_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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  ## Model description
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@@ -43,6 +63,60 @@ The following hyperparameters were used during training:
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  - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 50
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  ### Framework versions
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  - Transformers 4.36.0
 
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  base_model: facebook/wav2vec2-base
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: my_awesome_emotions_model
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.6086021505376344
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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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  # my_awesome_emotions_model
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3229
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+ - Accuracy: 0.6086
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  ## Model description
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  - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 50
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.7077 | 0.95 | 14 | 2.7049 | 0.0645 |
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+ | 2.7036 | 1.97 | 29 | 2.6957 | 0.0688 |
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+ | 2.6761 | 2.98 | 44 | 2.6471 | 0.1075 |
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+ | 2.6414 | 4.0 | 59 | 2.5442 | 0.1398 |
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+ | 2.5034 | 4.95 | 73 | 2.3988 | 0.2774 |
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+ | 2.4337 | 5.97 | 88 | 2.2798 | 0.3097 |
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+ | 2.2757 | 6.98 | 103 | 2.2054 | 0.3290 |
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+ | 2.2346 | 8.0 | 118 | 2.1204 | 0.3484 |
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+ | 2.1167 | 8.95 | 132 | 2.0784 | 0.3484 |
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+ | 2.0801 | 9.97 | 147 | 2.0267 | 0.3484 |
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+ | 1.987 | 10.98 | 162 | 1.9672 | 0.3699 |
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+ | 1.9278 | 12.0 | 177 | 1.9686 | 0.3505 |
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+ | 1.839 | 12.95 | 191 | 1.8604 | 0.4215 |
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+ | 1.785 | 13.97 | 206 | 1.8611 | 0.4129 |
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+ | 1.6811 | 14.98 | 221 | 1.7791 | 0.4473 |
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+ | 1.6858 | 16.0 | 236 | 1.7533 | 0.4323 |
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+ | 1.562 | 16.95 | 250 | 1.7364 | 0.4473 |
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+ | 1.5469 | 17.97 | 265 | 1.7407 | 0.4430 |
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+ | 1.485 | 18.98 | 280 | 1.7055 | 0.4301 |
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+ | 1.4489 | 20.0 | 295 | 1.6566 | 0.4839 |
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+ | 1.426 | 20.95 | 309 | 1.5844 | 0.5054 |
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+ | 1.3596 | 21.97 | 324 | 1.6252 | 0.4796 |
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+ | 1.3212 | 22.98 | 339 | 1.5797 | 0.4860 |
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+ | 1.248 | 24.0 | 354 | 1.5483 | 0.5097 |
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+ | 1.1954 | 24.95 | 368 | 1.5301 | 0.5290 |
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+ | 1.1629 | 25.97 | 383 | 1.4905 | 0.5398 |
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+ | 1.1364 | 26.98 | 398 | 1.5040 | 0.5355 |
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+ | 1.0897 | 28.0 | 413 | 1.5128 | 0.5484 |
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+ | 1.0564 | 28.95 | 427 | 1.4761 | 0.5570 |
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+ | 1.0149 | 29.97 | 442 | 1.4948 | 0.5247 |
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+ | 0.975 | 30.98 | 457 | 1.4194 | 0.5742 |
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+ | 0.9546 | 32.0 | 472 | 1.3986 | 0.5763 |
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+ | 0.9235 | 32.95 | 486 | 1.4126 | 0.5634 |
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+ | 0.8848 | 33.97 | 501 | 1.4284 | 0.5763 |
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+ | 0.8579 | 34.98 | 516 | 1.3872 | 0.5677 |
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+ | 0.8475 | 36.0 | 531 | 1.4108 | 0.5742 |
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+ | 0.8018 | 36.95 | 545 | 1.3667 | 0.5849 |
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+ | 0.7861 | 37.97 | 560 | 1.3614 | 0.5914 |
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+ | 0.7756 | 38.98 | 575 | 1.3473 | 0.5914 |
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+ | 0.7427 | 40.0 | 590 | 1.3346 | 0.5914 |
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+ | 0.764 | 40.95 | 604 | 1.3229 | 0.6086 |
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+ | 0.7283 | 41.97 | 619 | 1.3206 | 0.6 |
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+ | 0.714 | 42.98 | 634 | 1.3266 | 0.6065 |
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+ | 0.724 | 44.0 | 649 | 1.3377 | 0.5957 |
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+ | 0.6928 | 44.95 | 663 | 1.3281 | 0.5978 |
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+ | 0.7065 | 45.97 | 678 | 1.3214 | 0.6086 |
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+ | 0.6781 | 46.98 | 693 | 1.3338 | 0.5849 |
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+ | 0.7058 | 47.46 | 700 | 1.3330 | 0.5892 |
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+
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+
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  ### Framework versions
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  - Transformers 4.36.0
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