|
--- |
|
base_model: ylacombe/w2v-bert-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_16_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: w2v-bert-2.0-mongolian-colab-CV16.0 |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: common_voice_16_0 |
|
type: common_voice_16_0 |
|
config: mn |
|
split: test |
|
args: mn |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.3251033282575593 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# w2v-bert-2.0-mongolian-colab-CV16.0 |
|
|
|
This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5032 |
|
- Wer: 0.3251 |
|
|
|
## 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: 5e-05 |
|
- 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: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 3.7516 | 0.79 | 100 | 2.4041 | 1.0089 | |
|
| 1.0185 | 1.58 | 200 | 0.7642 | 0.6153 | |
|
| 0.5366 | 2.37 | 300 | 0.6518 | 0.5328 | |
|
| 0.4153 | 3.16 | 400 | 0.6116 | 0.4811 | |
|
| 0.353 | 3.95 | 500 | 0.6357 | 0.4806 | |
|
| 0.2876 | 4.74 | 600 | 0.6213 | 0.4434 | |
|
| 0.2389 | 5.53 | 700 | 0.5103 | 0.4243 | |
|
| 0.1735 | 6.32 | 800 | 0.5079 | 0.3753 | |
|
| 0.1419 | 7.11 | 900 | 0.5264 | 0.3638 | |
|
| 0.1031 | 7.91 | 1000 | 0.5454 | 0.3466 | |
|
| 0.0743 | 8.7 | 1100 | 0.5286 | 0.3337 | |
|
| 0.054 | 9.49 | 1200 | 0.5032 | 0.3251 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|