File size: 2,915 Bytes
4b0a79a 208fbea 1056d70 208fbea 4b0a79a 208fbea 1056d70 208fbea 1056d70 208fbea |
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/hubert-large-ll60k
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: speech_ocean_hubert_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_hubert_mdd
This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2027
- Wer: 0.0517
- Cer: 0.0499
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 42.7069 | 0.9873 | 39 | 36.7247 | 0.9992 | 0.9977 |
| 16.2787 | 2.0 | 79 | 7.8315 | 1.0 | 1.0 |
| 6.7896 | 2.9873 | 118 | 4.5645 | 1.0 | 1.0 |
| 4.0104 | 4.0 | 158 | 3.8654 | 1.0 | 1.0 |
| 3.8037 | 4.9873 | 197 | 3.8060 | 1.0 | 1.0 |
| 3.7898 | 6.0 | 237 | 3.7695 | 1.0 | 1.0 |
| 3.7777 | 6.9873 | 276 | 3.7717 | 1.0 | 1.0 |
| 3.7442 | 8.0 | 316 | 3.7320 | 1.0 | 1.0 |
| 3.7286 | 8.9873 | 355 | 3.6978 | 1.0 | 1.0 |
| 3.6272 | 10.0 | 395 | 3.5089 | 1.0 | 1.0 |
| 3.0921 | 10.9873 | 434 | 2.6068 | 0.9992 | 0.9997 |
| 2.2556 | 12.0 | 474 | 1.6832 | 0.5880 | 0.6815 |
| 1.7791 | 12.9873 | 513 | 1.2117 | 0.3861 | 0.4433 |
| 1.2731 | 14.0 | 553 | 0.7338 | 0.1793 | 0.1505 |
| 0.9596 | 14.9873 | 592 | 0.4892 | 0.1220 | 0.1005 |
| 0.7152 | 16.0 | 632 | 0.3525 | 0.0892 | 0.0752 |
| 0.521 | 16.9873 | 671 | 0.2843 | 0.0704 | 0.0623 |
| 0.4791 | 18.0 | 711 | 0.2351 | 0.0607 | 0.0568 |
| 0.3992 | 18.9873 | 750 | 0.2120 | 0.0547 | 0.0523 |
| 0.4245 | 19.7468 | 780 | 0.2027 | 0.0517 | 0.0499 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|