File size: 2,191 Bytes
9b0602a b880fbb 1118d77 4775d72 1118d77 157d55e 4775d72 1118d77 4775d72 b880fbb 4775d72 9b0602a 1118d77 9b0602a 1118d77 9b0602a b880fbb 1118d77 b7776a3 b880fbb 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 1118d77 9b0602a 157d55e b7776a3 9b0602a 1118d77 9b0602a 157d55e 1118d77 157d55e |
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 |
---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
base_model: nguyenvulebinh/wav2vec2-base-vi
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: wav2vec2-common-voice-16_1_vi
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_16_1
type: common_voice_16_1
config: vi
split: None
args: vi
metrics:
- type: wer
value: 0.9998983326555511
name: Wer
---
<!-- 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-common-voice-16_1_vi
This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5323
- Wer: 0.9999
## 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 21.7841 | 4.2373 | 500 | 7.6684 | 0.9999 |
| 4.0045 | 8.4746 | 1000 | 3.5474 | 0.9999 |
| 3.4763 | 12.7119 | 1500 | 3.5357 | 0.9999 |
| 3.4721 | 16.9492 | 2000 | 3.5319 | 0.9999 |
| 3.4661 | 21.1864 | 2500 | 3.5321 | 0.9999 |
| 3.464 | 25.4237 | 3000 | 3.5315 | 0.9999 |
| 3.4732 | 29.6610 | 3500 | 3.5323 | 0.9999 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|