File size: 3,583 Bytes
47b7466 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53-torgo-demo-f01-nolm
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. -->
# wav2vec2-large-xlsr-53-torgo-demo-f01-nolm
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.
It achieves the following results on the evaluation set:
- Loss: 0.0153
- Wer: 0.4756
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4166 | 0.81 | 500 | 4.5019 | 1.0 |
| 3.1088 | 1.62 | 1000 | 3.0459 | 1.0 |
| 2.8249 | 2.44 | 1500 | 3.0850 | 1.0 |
| 2.625 | 3.25 | 2000 | 2.6827 | 1.3656 |
| 1.9816 | 4.06 | 2500 | 1.6636 | 1.3701 |
| 1.3036 | 4.87 | 3000 | 0.9710 | 1.2504 |
| 0.9862 | 5.68 | 3500 | 0.6023 | 1.0519 |
| 0.7012 | 6.49 | 4000 | 0.4404 | 0.9342 |
| 0.6102 | 7.31 | 4500 | 0.3297 | 0.8491 |
| 0.5463 | 8.12 | 5000 | 0.2403 | 0.7773 |
| 0.4897 | 8.93 | 5500 | 0.1907 | 0.7335 |
| 0.4687 | 9.74 | 6000 | 0.1721 | 0.7095 |
| 0.41 | 10.55 | 6500 | 0.1382 | 0.6851 |
| 0.3277 | 11.36 | 7000 | 0.1189 | 0.6598 |
| 0.3182 | 12.18 | 7500 | 0.1040 | 0.6372 |
| 0.3279 | 12.99 | 8000 | 0.0961 | 0.6274 |
| 0.2735 | 13.8 | 8500 | 0.0806 | 0.5880 |
| 0.3153 | 14.61 | 9000 | 0.0821 | 0.5748 |
| 0.251 | 15.42 | 9500 | 0.0633 | 0.5437 |
| 0.2 | 16.23 | 10000 | 0.0534 | 0.5316 |
| 0.2134 | 17.05 | 10500 | 0.0475 | 0.5195 |
| 0.1727 | 17.86 | 11000 | 0.0435 | 0.5146 |
| 0.2143 | 18.67 | 11500 | 0.0406 | 0.5072 |
| 0.1679 | 19.48 | 12000 | 0.0386 | 0.5057 |
| 0.1836 | 20.29 | 12500 | 0.0359 | 0.4984 |
| 0.1542 | 21.1 | 13000 | 0.0284 | 0.4914 |
| 0.1672 | 21.92 | 13500 | 0.0289 | 0.4884 |
| 0.1526 | 22.73 | 14000 | 0.0256 | 0.4867 |
| 0.1263 | 23.54 | 14500 | 0.0247 | 0.4871 |
| 0.133 | 24.35 | 15000 | 0.0194 | 0.4816 |
| 0.1005 | 25.16 | 15500 | 0.0190 | 0.4798 |
| 0.1372 | 25.97 | 16000 | 0.0172 | 0.4786 |
| 0.1126 | 26.79 | 16500 | 0.0177 | 0.4773 |
| 0.0929 | 27.6 | 17000 | 0.0173 | 0.4775 |
| 0.1069 | 28.41 | 17500 | 0.0164 | 0.4773 |
| 0.0932 | 29.22 | 18000 | 0.0153 | 0.4756 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.0.0
- Tokenizers 0.13.2
|