update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,87 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- generated_from_trainer
|
| 4 |
+
datasets:
|
| 5 |
+
- audiofolder
|
| 6 |
+
metrics:
|
| 7 |
+
- accuracy
|
| 8 |
+
model-index:
|
| 9 |
+
- name: wav2vec2-base-random-stop-classification-4
|
| 10 |
+
results: []
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 14 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 15 |
+
|
| 16 |
+
# wav2vec2-base-random-stop-classification-4
|
| 17 |
+
|
| 18 |
+
This model is a fine-tuned version of [](https://huggingface.co/) on the audiofolder dataset.
|
| 19 |
+
It achieves the following results on the evaluation set:
|
| 20 |
+
- Loss: 0.3843
|
| 21 |
+
- Accuracy: 0.8706
|
| 22 |
+
|
| 23 |
+
## Model description
|
| 24 |
+
|
| 25 |
+
More information needed
|
| 26 |
+
|
| 27 |
+
## Intended uses & limitations
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Training and evaluation data
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training procedure
|
| 36 |
+
|
| 37 |
+
### Training hyperparameters
|
| 38 |
+
|
| 39 |
+
The following hyperparameters were used during training:
|
| 40 |
+
- learning_rate: 3e-05
|
| 41 |
+
- train_batch_size: 64
|
| 42 |
+
- eval_batch_size: 64
|
| 43 |
+
- seed: 42
|
| 44 |
+
- gradient_accumulation_steps: 4
|
| 45 |
+
- total_train_batch_size: 256
|
| 46 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 47 |
+
- lr_scheduler_type: linear
|
| 48 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 49 |
+
- num_epochs: 25
|
| 50 |
+
|
| 51 |
+
### Training results
|
| 52 |
+
|
| 53 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 54 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 55 |
+
| 0.6928 | 0.99 | 18 | 0.6588 | 0.6267 |
|
| 56 |
+
| 0.6746 | 1.97 | 36 | 0.5702 | 0.6969 |
|
| 57 |
+
| 0.5823 | 2.96 | 54 | 0.5035 | 0.7772 |
|
| 58 |
+
| 0.5573 | 4.0 | 73 | 0.4111 | 0.8188 |
|
| 59 |
+
| 0.5324 | 4.99 | 91 | 0.4359 | 0.7997 |
|
| 60 |
+
| 0.6058 | 5.97 | 109 | 0.4688 | 0.7875 |
|
| 61 |
+
| 0.4805 | 6.96 | 127 | 0.4055 | 0.8351 |
|
| 62 |
+
| 0.4641 | 8.0 | 146 | 0.4024 | 0.8351 |
|
| 63 |
+
| 0.4292 | 8.99 | 164 | 0.3913 | 0.8474 |
|
| 64 |
+
| 0.4217 | 9.97 | 182 | 0.3975 | 0.8522 |
|
| 65 |
+
| 0.3892 | 10.96 | 200 | 0.3808 | 0.8460 |
|
| 66 |
+
| 0.4056 | 12.0 | 219 | 0.4126 | 0.8515 |
|
| 67 |
+
| 0.3848 | 12.99 | 237 | 0.3602 | 0.8508 |
|
| 68 |
+
| 0.3698 | 13.97 | 255 | 0.3913 | 0.8488 |
|
| 69 |
+
| 0.3893 | 14.96 | 273 | 0.3611 | 0.8692 |
|
| 70 |
+
| 0.3341 | 16.0 | 292 | 0.3791 | 0.8624 |
|
| 71 |
+
| 0.3376 | 16.99 | 310 | 0.3578 | 0.8624 |
|
| 72 |
+
| 0.3331 | 17.97 | 328 | 0.3660 | 0.8658 |
|
| 73 |
+
| 0.3215 | 18.96 | 346 | 0.3817 | 0.8535 |
|
| 74 |
+
| 0.2982 | 20.0 | 365 | 0.4000 | 0.8658 |
|
| 75 |
+
| 0.2885 | 20.99 | 383 | 0.3674 | 0.8658 |
|
| 76 |
+
| 0.3124 | 21.97 | 401 | 0.3770 | 0.8672 |
|
| 77 |
+
| 0.2926 | 22.96 | 419 | 0.3779 | 0.8651 |
|
| 78 |
+
| 0.2941 | 24.0 | 438 | 0.3775 | 0.8733 |
|
| 79 |
+
| 0.2699 | 24.66 | 450 | 0.3843 | 0.8706 |
|
| 80 |
+
|
| 81 |
+
|
| 82 |
+
### Framework versions
|
| 83 |
+
|
| 84 |
+
- Transformers 4.27.4
|
| 85 |
+
- Pytorch 1.13.0
|
| 86 |
+
- Datasets 2.7.1
|
| 87 |
+
- Tokenizers 0.13.2
|