File size: 2,929 Bytes
29be462 8b4e2c1 29be462 8b4e2c1 |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: speech_ocean_wav2vec_mdd
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. -->
# speech_ocean_wav2vec_mdd
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3663
- Wer: 0.0863
- Cer: 0.0692
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 45.149 | 0.9873 | 39 | 45.0584 | 1.0258 | 0.7932 |
| 40.7325 | 2.0 | 79 | 32.0660 | 1.0 | 1.0 |
| 14.8164 | 2.9873 | 118 | 8.1694 | 1.0 | 1.0 |
| 5.6535 | 4.0 | 158 | 4.5922 | 1.0 | 1.0 |
| 3.9508 | 4.9873 | 197 | 3.8581 | 1.0 | 1.0 |
| 3.8065 | 6.0 | 237 | 3.7907 | 1.0 | 1.0 |
| 3.766 | 6.9873 | 276 | 3.7769 | 1.0 | 1.0 |
| 3.7552 | 8.0 | 316 | 3.7465 | 1.0 | 1.0 |
| 3.7489 | 8.9873 | 355 | 3.7611 | 1.0 | 1.0 |
| 3.7263 | 10.0 | 395 | 3.7234 | 1.0 | 1.0 |
| 3.7343 | 10.9873 | 434 | 3.6934 | 1.0 | 1.0 |
| 3.6327 | 12.0 | 474 | 3.4204 | 1.0 | 1.0 |
| 3.1861 | 12.9873 | 513 | 2.7907 | 0.9710 | 0.9864 |
| 2.2814 | 14.0 | 553 | 1.7142 | 0.5088 | 0.5401 |
| 1.6854 | 14.9873 | 592 | 1.0573 | 0.2488 | 0.1914 |
| 1.2968 | 16.0 | 632 | 0.7282 | 0.1786 | 0.1391 |
| 0.8626 | 16.9873 | 671 | 0.5435 | 0.1305 | 0.0999 |
| 0.7852 | 18.0 | 711 | 0.4440 | 0.1046 | 0.0831 |
| 0.6332 | 18.9873 | 750 | 0.3847 | 0.0936 | 0.0748 |
| 0.6518 | 19.7468 | 780 | 0.3663 | 0.0863 | 0.0692 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|