File size: 4,429 Bytes
dc58e92 a373bcb dc58e92 be17da2 dc58e92 aa6dd69 dc58e92 be17da2 dc58e92 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 |
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ft-wav2vec2-with-minds
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. -->
# ft-wav2vec2-with-minds
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0119
- Accuracy: 0.9972
## 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: 120
- eval_batch_size: 120
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 480
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.1595 | 1.0 | 9 | 5.2504 | 0.1125 |
| 3.706 | 2.0 | 18 | 1.7425 | 0.3261 |
| 1.1096 | 3.0 | 27 | 0.5152 | 0.7985 |
| 0.3567 | 4.0 | 36 | 0.1222 | 0.9728 |
| 0.1645 | 5.0 | 45 | 0.0988 | 0.9850 |
| 0.1539 | 6.0 | 54 | 0.0696 | 0.9878 |
| 0.1329 | 7.0 | 63 | 0.0783 | 0.9831 |
| 0.1023 | 8.0 | 72 | 0.0833 | 0.9841 |
| 0.1923 | 9.0 | 81 | 0.0733 | 0.9775 |
| 0.108 | 10.0 | 90 | 0.0294 | 0.9934 |
| 0.0884 | 11.0 | 99 | 0.0331 | 0.9897 |
| 0.1745 | 12.0 | 108 | 0.0288 | 0.9944 |
| 0.0793 | 13.0 | 117 | 0.0545 | 0.9869 |
| 0.0823 | 14.0 | 126 | 0.0551 | 0.9850 |
| 0.0857 | 15.0 | 135 | 0.0401 | 0.9925 |
| 0.0738 | 16.0 | 144 | 0.0329 | 0.9906 |
| 0.0905 | 17.0 | 153 | 0.0324 | 0.9878 |
| 0.1049 | 18.0 | 162 | 0.0379 | 0.9925 |
| 0.0775 | 19.0 | 171 | 0.0410 | 0.9906 |
| 0.07 | 20.0 | 180 | 0.0315 | 0.9925 |
| 0.0519 | 21.0 | 189 | 0.0361 | 0.9897 |
| 0.0679 | 22.0 | 198 | 0.0470 | 0.9878 |
| 0.0771 | 23.0 | 207 | 0.0258 | 0.9934 |
| 0.0588 | 24.0 | 216 | 0.0322 | 0.9934 |
| 0.0566 | 25.0 | 225 | 0.0251 | 0.9906 |
| 0.0665 | 26.0 | 234 | 0.0162 | 0.9963 |
| 0.06 | 27.0 | 243 | 0.0178 | 0.9953 |
| 0.0462 | 28.0 | 252 | 0.0183 | 0.9944 |
| 0.0527 | 29.0 | 261 | 0.0669 | 0.9831 |
| 0.0378 | 30.0 | 270 | 0.0163 | 0.9953 |
| 0.0418 | 31.0 | 279 | 0.0207 | 0.9963 |
| 0.0335 | 32.0 | 288 | 0.0159 | 0.9953 |
| 0.0447 | 33.0 | 297 | 0.0151 | 0.9963 |
| 0.0455 | 34.0 | 306 | 0.0161 | 0.9953 |
| 0.0368 | 35.0 | 315 | 0.0163 | 0.9944 |
| 0.043 | 36.0 | 324 | 0.0136 | 0.9963 |
| 0.0361 | 37.0 | 333 | 0.0181 | 0.9963 |
| 0.0374 | 38.0 | 342 | 0.0149 | 0.9963 |
| 0.0397 | 39.0 | 351 | 0.0119 | 0.9963 |
| 0.0329 | 40.0 | 360 | 0.0164 | 0.9953 |
| 0.0933 | 41.0 | 369 | 0.0119 | 0.9972 |
| 0.0311 | 42.0 | 378 | 0.0144 | 0.9963 |
| 0.0325 | 43.0 | 387 | 0.0131 | 0.9963 |
| 0.0418 | 44.0 | 396 | 0.0207 | 0.9963 |
| 0.0251 | 45.0 | 405 | 0.0178 | 0.9963 |
| 0.0409 | 46.0 | 414 | 0.0149 | 0.9953 |
| 0.0444 | 47.0 | 423 | 0.0155 | 0.9953 |
| 0.0318 | 48.0 | 432 | 0.0169 | 0.9953 |
| 0.0465 | 49.0 | 441 | 0.0171 | 0.9953 |
| 0.0308 | 50.0 | 450 | 0.0173 | 0.9953 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.12.1+cu116
- Datasets 2.15.0
- Tokenizers 0.15.2
|