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---

license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SER_model_xapiens_binary
  results: []
---


<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# SER_model_xapiens_binary



This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.

It achieves the following results on the evaluation set:

- Loss: 1.9238

- Accuracy: 0.6121



## Model description



More information needed



## Intended uses & limitations



More information needed



## Training and evaluation data



More information needed



## Training procedure



### Training hyperparameters



The following hyperparameters were used during training:

- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256

- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08

- lr_scheduler_type: linear

- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100



### Training results



| Training Loss | Epoch | Step | Validation Loss | Accuracy |

|:-------------:|:-----:|:----:|:---------------:|:--------:|

| No log        | 1.0   | 9    | 0.6576          | 0.6186   |

| 0.6373        | 2.0   | 18   | 0.6570          | 0.6239   |

| 0.6356        | 3.0   | 27   | 0.6528          | 0.6252   |

| 0.6255        | 4.0   | 36   | 0.6525          | 0.6212   |

| 0.6275        | 5.0   | 45   | 0.6459          | 0.6239   |

| 0.62          | 6.0   | 54   | 0.6564          | 0.6252   |

| 0.6079        | 7.0   | 63   | 0.6575          | 0.6173   |

| 0.6066        | 8.0   | 72   | 0.6592          | 0.6304   |

| 0.6032        | 9.0   | 81   | 0.6540          | 0.6265   |

| 0.5894        | 10.0  | 90   | 0.6553          | 0.6252   |

| 0.5894        | 11.0  | 99   | 0.6764          | 0.6239   |

| 0.5707        | 12.0  | 108  | 0.6768          | 0.6370   |

| 0.5665        | 13.0  | 117  | 0.6877          | 0.6330   |

| 0.5478        | 14.0  | 126  | 0.7169          | 0.6134   |

| 0.5303        | 15.0  | 135  | 0.7437          | 0.5767   |

| 0.5113        | 16.0  | 144  | 0.7235          | 0.6252   |

| 0.4867        | 17.0  | 153  | 0.7914          | 0.6055   |

| 0.4525        | 18.0  | 162  | 0.7906          | 0.6121   |

| 0.4339        | 19.0  | 171  | 0.7946          | 0.6029   |

| 0.4231        | 20.0  | 180  | 0.7982          | 0.6121   |

| 0.4231        | 21.0  | 189  | 0.7991          | 0.6278   |

| 0.3913        | 22.0  | 198  | 0.8757          | 0.6252   |

| 0.3967        | 23.0  | 207  | 0.8746          | 0.6042   |

| 0.3615        | 24.0  | 216  | 0.8731          | 0.5976   |

| 0.3354        | 25.0  | 225  | 0.9350          | 0.6173   |

| 0.3288        | 26.0  | 234  | 0.9604          | 0.6042   |

| 0.3087        | 27.0  | 243  | 0.9534          | 0.6199   |

| 0.2977        | 28.0  | 252  | 0.9491          | 0.6107   |

| 0.2657        | 29.0  | 261  | 1.0096          | 0.6134   |

| 0.2614        | 30.0  | 270  | 1.0069          | 0.6042   |

| 0.2614        | 31.0  | 279  | 1.0388          | 0.5990   |

| 0.2309        | 32.0  | 288  | 1.1028          | 0.5950   |

| 0.2155        | 33.0  | 297  | 1.1211          | 0.6239   |

| 0.2162        | 34.0  | 306  | 1.1376          | 0.5767   |

| 0.2055        | 35.0  | 315  | 1.2133          | 0.5806   |

| 0.1949        | 36.0  | 324  | 1.1371          | 0.5963   |

| 0.1897        | 37.0  | 333  | 1.2791          | 0.5793   |

| 0.1715        | 38.0  | 342  | 1.2176          | 0.5924   |

| 0.1622        | 39.0  | 351  | 1.2985          | 0.5832   |

| 0.1571        | 40.0  | 360  | 1.3201          | 0.5832   |

| 0.1571        | 41.0  | 369  | 1.3364          | 0.5976   |

| 0.1518        | 42.0  | 378  | 1.2600          | 0.6173   |

| 0.1715        | 43.0  | 387  | 1.2334          | 0.6134   |

| 0.1702        | 44.0  | 396  | 1.2732          | 0.6055   |

| 0.1292        | 45.0  | 405  | 1.3833          | 0.5963   |

| 0.1104        | 46.0  | 414  | 1.4520          | 0.5990   |

| 0.1572        | 47.0  | 423  | 1.3802          | 0.6291   |

| 0.132         | 48.0  | 432  | 1.4400          | 0.6003   |

| 0.1528        | 49.0  | 441  | 1.3557          | 0.6212   |

| 0.1219        | 50.0  | 450  | 1.3858          | 0.5911   |

| 0.1219        | 51.0  | 459  | 1.4453          | 0.5937   |

| 0.1014        | 52.0  | 468  | 1.3600          | 0.6212   |

| 0.0951        | 53.0  | 477  | 1.4042          | 0.6186   |

| 0.0962        | 54.0  | 486  | 1.4200          | 0.6199   |

| 0.0937        | 55.0  | 495  | 1.4017          | 0.6291   |

| 0.1005        | 56.0  | 504  | 1.4544          | 0.6081   |

| 0.0832        | 57.0  | 513  | 1.4527          | 0.6252   |

| 0.0896        | 58.0  | 522  | 1.4970          | 0.6068   |

| 0.0754        | 59.0  | 531  | 1.5413          | 0.6016   |

| 0.076         | 60.0  | 540  | 1.5303          | 0.6186   |

| 0.076         | 61.0  | 549  | 1.5076          | 0.6134   |

| 0.0945        | 62.0  | 558  | 1.4725          | 0.6225   |

| 0.0636        | 63.0  | 567  | 1.5103          | 0.6160   |

| 0.0866        | 64.0  | 576  | 1.5384          | 0.6304   |

| 0.0558        | 65.0  | 585  | 1.5868          | 0.6081   |

| 0.0607        | 66.0  | 594  | 1.5560          | 0.6265   |

| 0.0595        | 67.0  | 603  | 1.6161          | 0.6212   |

| 0.0566        | 68.0  | 612  | 1.6855          | 0.5911   |

| 0.042         | 69.0  | 621  | 1.6898          | 0.6186   |

| 0.0506        | 70.0  | 630  | 1.6505          | 0.6330   |

| 0.0506        | 71.0  | 639  | 1.6898          | 0.6107   |

| 0.048         | 72.0  | 648  | 1.6370          | 0.6225   |

| 0.0564        | 73.0  | 657  | 1.6576          | 0.6147   |

| 0.0512        | 74.0  | 666  | 1.7149          | 0.6003   |

| 0.0482        | 75.0  | 675  | 1.7085          | 0.6199   |

| 0.0351        | 76.0  | 684  | 1.7413          | 0.6134   |

| 0.0432        | 77.0  | 693  | 1.7627          | 0.6016   |

| 0.0368        | 78.0  | 702  | 1.7961          | 0.6291   |

| 0.0416        | 79.0  | 711  | 1.7539          | 0.6199   |

| 0.0398        | 80.0  | 720  | 1.7764          | 0.6160   |

| 0.0398        | 81.0  | 729  | 1.8516          | 0.6252   |

| 0.0311        | 82.0  | 738  | 1.8629          | 0.6199   |

| 0.0327        | 83.0  | 747  | 1.8564          | 0.6147   |

| 0.0404        | 84.0  | 756  | 1.8447          | 0.6291   |

| 0.0407        | 85.0  | 765  | 1.8198          | 0.6173   |

| 0.0432        | 86.0  | 774  | 1.8477          | 0.6029   |

| 0.0367        | 87.0  | 783  | 1.8972          | 0.6317   |

| 0.0334        | 88.0  | 792  | 1.8497          | 0.6121   |

| 0.0228        | 89.0  | 801  | 1.8638          | 0.6199   |

| 0.0351        | 90.0  | 810  | 1.8128          | 0.6107   |

| 0.0351        | 91.0  | 819  | 1.8479          | 0.6186   |

| 0.0342        | 92.0  | 828  | 1.8849          | 0.6225   |

| 0.0257        | 93.0  | 837  | 1.9021          | 0.6160   |

| 0.0288        | 94.0  | 846  | 1.9284          | 0.6147   |

| 0.0241        | 95.0  | 855  | 1.9315          | 0.6107   |

| 0.0237        | 96.0  | 864  | 1.9235          | 0.5976   |

| 0.0231        | 97.0  | 873  | 1.9428          | 0.6225   |

| 0.0217        | 98.0  | 882  | 1.9266          | 0.6199   |

| 0.0215        | 99.0  | 891  | 1.9238          | 0.6160   |

| 0.0207        | 100.0 | 900  | 1.9238          | 0.6121   |





### Framework versions



- Transformers 4.42.0.dev0

- Pytorch 2.3.0

- Datasets 2.19.2.dev0

- Tokenizers 0.19.1