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Krithika-p
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my_awesome_mind_model

Audio Classification
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wav2vec2
Generated from Trainer
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End of training

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Files changed (3) hide show
  1. README.md +48 -19
  2. model.safetensors +1 -1
  3. runs/Dec09_19-56-18_d8a0ab846198/events.out.tfevents.1702151778.d8a0ab846198.583.1 +2 -2
README.md CHANGED
@@ -4,7 +4,7 @@ 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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- - minds14
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  metrics:
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  - accuracy
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  model-index:
@@ -14,15 +14,15 @@ model-index:
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  name: Audio Classification
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  type: audio-classification
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  dataset:
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- name: minds14
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- type: minds14
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- config: en-US
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- split: train
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- args: en-US
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.08849557522123894
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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
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # my_awesome_mind_model
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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: nan
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- - Accuracy: 0.0885
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  ## Model description
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@@ -61,20 +61,49 @@ The following hyperparameters were used during training:
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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_ratio: 0.1
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- - num_epochs: 10
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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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- | No log | 0.8 | 3 | 2.6371 | 0.0708 |
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- | No log | 1.87 | 7 | nan | 0.0885 |
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- | 24.6937 | 2.93 | 11 | nan | 0.0885 |
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- | 24.6937 | 4.0 | 15 | nan | 0.0885 |
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- | 24.6937 | 4.8 | 18 | nan | 0.0885 |
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- | 0.0 | 5.87 | 22 | nan | 0.0885 |
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- | 0.0 | 6.93 | 26 | nan | 0.0885 |
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- | 0.0 | 8.0 | 30 | nan | 0.0885 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 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: 0.2793103448275862
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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_mind_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: 2.3078
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+ - Accuracy: 0.2793
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  ## Model description
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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_ratio: 0.1
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+ - num_epochs: 50
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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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+ | No log | 0.73 | 2 | 2.6832 | 0.1241 |
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+ | No log | 1.82 | 5 | 2.6800 | 0.1103 |
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+ | No log | 2.91 | 8 | 2.6726 | 0.1207 |
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+ | 2.6498 | 4.0 | 11 | 2.6580 | 0.1483 |
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+ | 2.6498 | 4.73 | 13 | 2.6454 | 0.1379 |
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+ | 2.6498 | 5.82 | 16 | 2.6245 | 0.1379 |
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+ | 2.6498 | 6.91 | 19 | 2.6038 | 0.1414 |
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+ | 2.6057 | 8.0 | 22 | 2.5839 | 0.1552 |
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+ | 2.6057 | 8.73 | 24 | 2.5656 | 0.1655 |
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+ | 2.6057 | 9.82 | 27 | 2.5378 | 0.1552 |
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+ | 2.524 | 10.91 | 30 | 2.5192 | 0.1862 |
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+ | 2.524 | 12.0 | 33 | 2.4996 | 0.1931 |
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+ | 2.524 | 12.73 | 35 | 2.4900 | 0.2069 |
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+ | 2.524 | 13.82 | 38 | 2.4663 | 0.2138 |
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+ | 2.4304 | 14.91 | 41 | 2.4498 | 0.2207 |
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+ | 2.4304 | 16.0 | 44 | 2.4309 | 0.2138 |
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+ | 2.4304 | 16.73 | 46 | 2.4291 | 0.2310 |
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+ | 2.4304 | 17.82 | 49 | 2.4106 | 0.2517 |
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+ | 2.3519 | 18.91 | 52 | 2.3944 | 0.2310 |
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+ | 2.3519 | 20.0 | 55 | 2.3949 | 0.2414 |
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+ | 2.3519 | 20.73 | 57 | 2.3807 | 0.2414 |
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+ | 2.2774 | 21.82 | 60 | 2.3661 | 0.2379 |
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+ | 2.2774 | 22.91 | 63 | 2.3600 | 0.2345 |
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+ | 2.2774 | 24.0 | 66 | 2.3572 | 0.2483 |
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+ | 2.2774 | 24.73 | 68 | 2.3430 | 0.2345 |
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+ | 2.2402 | 25.82 | 71 | 2.3369 | 0.2586 |
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+ | 2.2402 | 26.91 | 74 | 2.3365 | 0.2586 |
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+ | 2.2402 | 28.0 | 77 | 2.3301 | 0.2621 |
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+ | 2.2402 | 28.73 | 79 | 2.3274 | 0.2724 |
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+ | 2.1901 | 29.82 | 82 | 2.3266 | 0.2759 |
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+ | 2.1901 | 30.91 | 85 | 2.3207 | 0.2655 |
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+ | 2.1901 | 32.0 | 88 | 2.3115 | 0.2724 |
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+ | 2.148 | 32.73 | 90 | 2.3084 | 0.2724 |
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+ | 2.148 | 33.82 | 93 | 2.3082 | 0.2724 |
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+ | 2.148 | 34.91 | 96 | 2.3094 | 0.2828 |
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+ | 2.148 | 36.0 | 99 | 2.3080 | 0.2793 |
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+ | 2.1303 | 36.36 | 100 | 2.3078 | 0.2793 |
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  ### Framework versions
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