Alikhan Urumov commited on
Commit ·
45e8a37
1
Parent(s): 50adf86
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,106 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
model-index:
|
| 6 |
+
- name: wav2vec2-russian
|
| 7 |
+
results: []
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 11 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 12 |
+
|
| 13 |
+
# wav2vec2-russian
|
| 14 |
+
|
| 15 |
+
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
|
| 16 |
+
It achieves the following results on the evaluation set:
|
| 17 |
+
- Loss: 1.2210
|
| 18 |
+
- Wer: 0.4966
|
| 19 |
+
|
| 20 |
+
## Model description
|
| 21 |
+
|
| 22 |
+
More information needed
|
| 23 |
+
|
| 24 |
+
## Intended uses & limitations
|
| 25 |
+
|
| 26 |
+
More information needed
|
| 27 |
+
|
| 28 |
+
## Training and evaluation data
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Training procedure
|
| 33 |
+
|
| 34 |
+
### Training hyperparameters
|
| 35 |
+
|
| 36 |
+
The following hyperparameters were used during training:
|
| 37 |
+
- learning_rate: 0.0001
|
| 38 |
+
- train_batch_size: 16
|
| 39 |
+
- eval_batch_size: 8
|
| 40 |
+
- seed: 42
|
| 41 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 42 |
+
- lr_scheduler_type: linear
|
| 43 |
+
- lr_scheduler_warmup_steps: 1000
|
| 44 |
+
- num_epochs: 12
|
| 45 |
+
- mixed_precision_training: Native AMP
|
| 46 |
+
|
| 47 |
+
### Training results
|
| 48 |
+
|
| 49 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
| 50 |
+
|:-------------:|:-----:|:-----:|:---------------:|:------:|
|
| 51 |
+
| 5.0548 | 0.25 | 500 | 4.1857 | 0.9999 |
|
| 52 |
+
| 3.0204 | 0.5 | 1000 | 1.9996 | 0.9998 |
|
| 53 |
+
| 1.8692 | 0.74 | 1500 | 1.6426 | 0.8698 |
|
| 54 |
+
| 1.5154 | 0.99 | 2000 | 1.6156 | 0.7481 |
|
| 55 |
+
| 1.3677 | 1.24 | 2500 | 2.1281 | 0.7120 |
|
| 56 |
+
| 1.3223 | 1.49 | 3000 | 1.5192 | 0.6846 |
|
| 57 |
+
| 1.2512 | 1.73 | 3500 | 1.0993 | 0.6634 |
|
| 58 |
+
| 1.2257 | 1.98 | 4000 | 1.1039 | 0.6493 |
|
| 59 |
+
| 1.1418 | 2.23 | 4500 | 1.0170 | 0.6241 |
|
| 60 |
+
| 1.1213 | 2.48 | 5000 | 0.8436 | 0.6191 |
|
| 61 |
+
| 1.112 | 2.73 | 5500 | 0.7326 | 0.6102 |
|
| 62 |
+
| 1.0912 | 2.97 | 6000 | 0.7054 | 0.5976 |
|
| 63 |
+
| 1.0465 | 3.22 | 6500 | 1.0887 | 0.5941 |
|
| 64 |
+
| 1.0215 | 3.47 | 7000 | 1.4577 | 0.5793 |
|
| 65 |
+
| 1.0244 | 3.72 | 7500 | 1.6058 | 0.5855 |
|
| 66 |
+
| 1.0254 | 3.96 | 8000 | 1.3366 | 0.5750 |
|
| 67 |
+
| 0.9558 | 4.21 | 8500 | 0.8088 | 0.5644 |
|
| 68 |
+
| 0.966 | 4.46 | 9000 | 0.9650 | 0.5636 |
|
| 69 |
+
| 0.9674 | 4.71 | 9500 | 0.9047 | 0.5532 |
|
| 70 |
+
| 0.9373 | 4.96 | 10000 | 1.0342 | 0.5422 |
|
| 71 |
+
| 0.9126 | 5.2 | 10500 | 1.2346 | 0.5462 |
|
| 72 |
+
| 0.9063 | 5.45 | 11000 | 1.2696 | 0.5412 |
|
| 73 |
+
| 0.9126 | 5.7 | 11500 | 1.4693 | 0.5317 |
|
| 74 |
+
| 0.8936 | 5.95 | 12000 | 1.9096 | 0.5369 |
|
| 75 |
+
| 0.8621 | 6.19 | 12500 | 1.6382 | 0.5326 |
|
| 76 |
+
| 0.8695 | 6.44 | 13000 | 0.9466 | 0.5252 |
|
| 77 |
+
| 0.8423 | 6.69 | 13500 | 1.6286 | 0.5355 |
|
| 78 |
+
| 0.8494 | 6.94 | 14000 | 0.8368 | 0.5264 |
|
| 79 |
+
| 0.8354 | 7.19 | 14500 | 0.6893 | 0.5216 |
|
| 80 |
+
| 0.8133 | 7.43 | 15000 | 0.5916 | 0.5175 |
|
| 81 |
+
| 0.8147 | 7.68 | 15500 | 0.7813 | 0.5221 |
|
| 82 |
+
| 0.8258 | 7.93 | 16000 | 1.3814 | 0.5129 |
|
| 83 |
+
| 0.8079 | 8.18 | 16500 | 0.8368 | 0.5176 |
|
| 84 |
+
| 0.7868 | 8.42 | 17000 | 0.9456 | 0.5159 |
|
| 85 |
+
| 0.7955 | 8.67 | 17500 | 0.7412 | 0.5170 |
|
| 86 |
+
| 0.7921 | 8.92 | 18000 | 0.6256 | 0.5066 |
|
| 87 |
+
| 0.7536 | 9.17 | 18500 | 0.8792 | 0.5101 |
|
| 88 |
+
| 0.7667 | 9.42 | 19000 | 1.0615 | 0.5032 |
|
| 89 |
+
| 0.772 | 9.66 | 19500 | 1.1312 | 0.5086 |
|
| 90 |
+
| 0.7418 | 9.91 | 20000 | 1.3485 | 0.4990 |
|
| 91 |
+
| 0.7577 | 10.16 | 20500 | 1.0788 | 0.5037 |
|
| 92 |
+
| 0.7311 | 10.41 | 21000 | 0.9978 | 0.5032 |
|
| 93 |
+
| 0.7419 | 10.65 | 21500 | 1.3925 | 0.5017 |
|
| 94 |
+
| 0.74 | 10.9 | 22000 | 1.4191 | 0.4981 |
|
| 95 |
+
| 0.7297 | 11.15 | 22500 | 1.1082 | 0.4994 |
|
| 96 |
+
| 0.737 | 11.4 | 23000 | 1.1208 | 0.4971 |
|
| 97 |
+
| 0.7266 | 11.65 | 23500 | 1.1595 | 0.4952 |
|
| 98 |
+
| 0.7091 | 11.89 | 24000 | 1.2210 | 0.4966 |
|
| 99 |
+
|
| 100 |
+
|
| 101 |
+
### Framework versions
|
| 102 |
+
|
| 103 |
+
- Transformers 4.17.0
|
| 104 |
+
- Pytorch 1.10.0+cu111
|
| 105 |
+
- Datasets 2.0.0
|
| 106 |
+
- Tokenizers 0.11.6
|