File size: 4,241 Bytes
9ceac0d |
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 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 |
---
language:
- vi
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- ducha07/audio_HTV_thoisu
metrics:
- wer
model-index:
- name: ASR4-for-40-epochs
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: HTV news
type: ducha07/audio_HTV_thoisu
metrics:
- name: Wer
type: wer
value: 0.26843348202571504
---
<!-- 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. -->
# ASR4-for-40-epochs
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the HTV news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4791
- Wer: 0.2684
## 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: 0.001
- train_batch_size: 32
- 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: 100
- num_epochs: 40
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.1111 | 0.92 | 100 | 0.7687 | 0.4387 |
| 1.1201 | 1.83 | 200 | 0.6388 | 0.3767 |
| 0.9734 | 2.75 | 300 | 0.6319 | 0.3658 |
| 0.9297 | 3.67 | 400 | 0.5740 | 0.3373 |
| 0.9142 | 4.59 | 500 | 0.5591 | 0.3268 |
| 0.8462 | 5.5 | 600 | 0.5627 | 0.3227 |
| 0.8366 | 6.42 | 700 | 0.5491 | 0.3158 |
| 0.8272 | 7.34 | 800 | 0.5398 | 0.3243 |
| 0.8137 | 8.26 | 900 | 0.5363 | 0.3113 |
| 0.7643 | 9.17 | 1000 | 0.5528 | 0.3117 |
| 0.7738 | 10.09 | 1100 | 0.5194 | 0.3285 |
| 0.7622 | 11.01 | 1200 | 0.5348 | 0.3043 |
| 0.707 | 11.93 | 1300 | 0.5179 | 0.2909 |
| 0.7242 | 12.84 | 1400 | 0.5153 | 0.3138 |
| 0.7093 | 13.76 | 1500 | 0.5116 | 0.2951 |
| 0.673 | 14.68 | 1600 | 0.5002 | 0.2941 |
| 0.6877 | 15.6 | 1700 | 0.4958 | 0.3050 |
| 0.6665 | 16.51 | 1800 | 0.5032 | 0.2865 |
| 0.6507 | 17.43 | 1900 | 0.4871 | 0.2809 |
| 0.6308 | 18.35 | 2000 | 0.4953 | 0.2947 |
| 0.6507 | 19.27 | 2100 | 0.4998 | 0.2837 |
| 0.6027 | 20.18 | 2200 | 0.4963 | 0.2868 |
| 0.623 | 21.1 | 2300 | 0.4955 | 0.2953 |
| 0.6047 | 22.02 | 2400 | 0.5034 | 0.2852 |
| 0.5825 | 22.94 | 2500 | 0.4781 | 0.2795 |
| 0.585 | 23.85 | 2600 | 0.4851 | 0.2843 |
| 0.5838 | 24.77 | 2700 | 0.4957 | 0.2742 |
| 0.5718 | 25.69 | 2800 | 0.4885 | 0.2810 |
| 0.5646 | 26.61 | 2900 | 0.4778 | 0.2724 |
| 0.5476 | 27.52 | 3000 | 0.4914 | 0.2751 |
| 0.5333 | 28.44 | 3100 | 0.4879 | 0.2788 |
| 0.5533 | 29.36 | 3200 | 0.4820 | 0.2726 |
| 0.5321 | 30.28 | 3300 | 0.4816 | 0.2686 |
| 0.5161 | 31.19 | 3400 | 0.4865 | 0.2812 |
| 0.5326 | 32.11 | 3500 | 0.4818 | 0.2704 |
| 0.5188 | 33.03 | 3600 | 0.4816 | 0.2669 |
| 0.506 | 33.94 | 3700 | 0.4804 | 0.2755 |
| 0.5122 | 34.86 | 3800 | 0.4803 | 0.2667 |
| 0.506 | 35.78 | 3900 | 0.4785 | 0.2708 |
| 0.5064 | 36.7 | 4000 | 0.4755 | 0.2730 |
| 0.4997 | 37.61 | 4100 | 0.4804 | 0.2708 |
| 0.4904 | 38.53 | 4200 | 0.4772 | 0.2678 |
| 0.4774 | 39.45 | 4300 | 0.4791 | 0.2684 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|